How to achieve the results of the paper？

[torchmyheart]

Hello, thank you very much for your work and code, I have a few questions that I am puzzled and hope you can help me.
I trained the small deit many times according to the parameters you gave, but the best results obtained on the CUB validation set are as follows:
Cls@1:0.782 Cls@5:0.945
Loc@1:0.626 Loc@5:0.764 Loc_gt:0.804

And the results given in the paper are:
Loc.Acc@1: 71.3 Loc.Acc@5: 83.8
Loc.Gt-Known: 87.7 Cls.Acc@1: 80.3 Cls.Acc@5: 94.8

How can I get the results in your paper? By increasing the number of iterations?
Thank you again, and look forward to your answers.

[vasgaowei]

Hi, thank you for your interest in our work. Could you please show me the training log?

[torchmyheart]

Thank you very much for your reply. This is my training log. I look forward to your reply very much.

{'BASIC': {'BACKUP_CODES': True,
'BACKUP_LIST': ['lib', 'tools_cam', 'configs'],
'DISP_FREQ': 10,
'GPU_ID': [0],
'NUM_WORKERS': 40,
'ROOT_DIR': './tools_cam/..',
'SAVE_DIR': '/data1/sungy/projectdata/TS-CAM-master/ckpt/CUB/deit_tscam_small_patch16_224_CAM-NORMAL_SEED26_CAM-THR0.1_BS128_2021-09-07-19-27',
'SEED': 26,
'TIME': '2021-09-07-19-27'},
'CUDNN': {'BENCHMARK': False, 'DETERMINISTIC': True, 'ENABLE': True},
'DATA': {'CROP_SIZE': 224,
'DATADIR': '/data1/sungy/dataset/CUB_200_2011',
'DATASET': 'CUB',
'IMAGE_MEAN': [0.485, 0.456, 0.406],
'IMAGE_STD': [0.229, 0.224, 0.225],
'NUM_CLASSES': 200,
'RESIZE_SIZE': 256,
'SCALE_LENGTH': 15,
'SCALE_SIZE': 196},
'MODEL': {'ARCH': 'deit_tscam_small_patch16_224',
'CAM_THR': 0.1,
'LOCALIZER_DIR': '',
'TOP_K': 1},
'SOLVER': {'LR_FACTOR': 0.1,
'LR_STEPS': [30],
'MUMENTUM': 0.9,
'NUM_EPOCHS': 60,
'START_LR': 0.001,
'WEIGHT_DECAY': 0.0005},
'TEST': {'BATCH_SIZE': 128,
'CKPT_DIR': '',
'SAVE_BOXED_IMAGE': False,
'SAVE_CAMS': False,
'TEN_CROPS': False},
'TRAIN': {'ALPHA': 1.0, 'BATCH_SIZE': 128, 'BETA': 1.0}}
==> Preparing data...
done!
==> Preparing networks for baseline...
Removing key head.weight from pretrained checkpoint
Removing key head.bias from pretrained checkpoint
TSCAM(
(patch_embed): PatchEmbed(
(proj): Conv2d(3, 384, kernel_size=(16, 16), stride=(16, 16))
)
(pos_drop): Dropout(p=0.0, inplace=False)
(blocks): ModuleList(
(0): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): Identity()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(1): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(2): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(3): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(4): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(5): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(6): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(7): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(8): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(9): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(10): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(11): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
)
(norm): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(head): Conv2d(384, 200, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(avgpool): AdaptiveAvgPool2d(output_size=1)
)
Preparing networks done!
Train Epoch: [1][1/47],lr: 0.00005 Loss 5.3981 (5.3981) Prec@1 0.781 (0.781) Prec@5 3.125 (3.125)
Train Epoch: [1][11/47],lr: 0.00005 Loss 5.2514 (5.3271) Prec@1 3.125 (1.349) Prec@5 5.469 (3.480)
Train Epoch: [1][21/47],lr: 0.00005 Loss 5.2075 (5.2790) Prec@1 2.344 (1.525) Prec@5 6.250 (5.060)
Train Epoch: [1][31/47],lr: 0.00005 Loss 4.9518 (5.2187) Prec@1 5.469 (2.016) Prec@5 18.750 (6.956)
Train Epoch: [1][41/47],lr: 0.00005 Loss 4.6554 (5.1187) Prec@1 7.031 (3.392) Prec@5 24.219 (11.033)
Train Epoch: [1][47/47],lr: 0.00005 Loss 4.4729 (5.0439) Prec@1 14.151 (4.371) Prec@5 26.415 (13.530)
Val Epoch: [1][1/46] Loss 3.7862 (3.7862)
Cls@1:0.383 Cls@5:0.695
Loc@1:0.258 Loc@5:0.531 Loc_gt:0.719

Val Epoch: [1][11/46] Loss 3.5845 (4.2272)
Cls@1:0.201 Cls@5:0.441
Loc@1:0.132 Loc@5:0.275 Loc_gt:0.491

Val Epoch: [1][21/46] Loss 4.3596 (4.1427)
Cls@1:0.206 Cls@5:0.483
Loc@1:0.144 Loc@5:0.318 Loc_gt:0.525

Val Epoch: [1][31/46] Loss 4.7249 (4.2272)
Cls@1:0.178 Cls@5:0.441
Loc@1:0.125 Loc@5:0.287 Loc_gt:0.498

Val Epoch: [1][41/46] Loss 4.1365 (4.2056)
Cls@1:0.163 Cls@5:0.431
Loc@1:0.113 Loc@5:0.279 Loc_gt:0.511

Val Epoch: [1][46/46] Loss 3.8258 (4.2103)
Cls@1:0.172 Cls@5:0.443
Loc@1:0.116 Loc@5:0.279 Loc_gt:0.500

wrong_details:675 4796 0 104 215 4
Best GT_LOC: 0.49982740766309974
Best TOP1_LOC: 0.49982740766309974
2021-09-07-19-30
Train Epoch: [2][1/47],lr: 0.00005 Loss 4.1711 (4.1711) Prec@1 25.781 (25.781) Prec@5 53.906 (53.906)
Train Epoch: [2][11/47],lr: 0.00005 Loss 3.6475 (3.9957) Prec@1 28.906 (25.923) Prec@5 57.812 (55.043)
Train Epoch: [2][21/47],lr: 0.00005 Loss 3.4617 (3.7989) Prec@1 33.594 (28.162) Prec@5 69.531 (58.482)
Train Epoch: [2][31/47],lr: 0.00005 Loss 3.2217 (3.6163) Prec@1 35.938 (30.746) Prec@5 64.062 (61.593)
Train Epoch: [2][41/47],lr: 0.00005 Loss 2.8129 (3.4415) Prec@1 47.656 (34.337) Prec@5 72.656 (64.729)
Train Epoch: [2][47/47],lr: 0.00005 Loss 2.8763 (3.3629) Prec@1 39.623 (35.602) Prec@5 74.528 (66.200)
Val Epoch: [2][1/46] Loss 2.3422 (2.3422)
Cls@1:0.477 Cls@5:0.875
Loc@1:0.406 Loc@5:0.766 Loc_gt:0.883

Val Epoch: [2][11/46] Loss 2.1293 (2.3069)
Cls@1:0.509 Cls@5:0.836
Loc@1:0.426 Loc@5:0.700 Loc_gt:0.830

Val Epoch: [2][21/46] Loss 2.3213 (2.2064)
Cls@1:0.549 Cls@5:0.855
Loc@1:0.465 Loc@5:0.726 Loc_gt:0.841

Val Epoch: [2][31/46] Loss 3.0397 (2.3571)
Cls@1:0.509 Cls@5:0.824
Loc@1:0.425 Loc@5:0.688 Loc_gt:0.823

Val Epoch: [2][41/46] Loss 2.9791 (2.4049)
Cls@1:0.493 Cls@5:0.820
Loc@1:0.409 Loc@5:0.678 Loc_gt:0.816

Val Epoch: [2][46/46] Loss 3.0392 (2.3830)
Cls@1:0.507 Cls@5:0.824
Loc@1:0.421 Loc@5:0.683 Loc_gt:0.818

wrong_details:2439 2857 0 408 84 6
Best GT_LOC: 0.8175698998964446
Best TOP1_LOC: 0.8175698998964446
2021-09-07-19-31
Train Epoch: [3][1/47],lr: 0.00005 Loss 2.4557 (2.4557) Prec@1 58.594 (58.594) Prec@5 83.594 (83.594)
Train Epoch: [3][11/47],lr: 0.00005 Loss 2.3504 (2.3358) Prec@1 60.156 (59.446) Prec@5 86.719 (85.440)
Train Epoch: [3][21/47],lr: 0.00005 Loss 2.2717 (2.2661) Prec@1 52.344 (59.635) Prec@5 82.812 (86.161)
Train Epoch: [3][31/47],lr: 0.00005 Loss 1.8601 (2.1618) Prec@1 66.406 (61.114) Prec@5 92.188 (87.450)
Train Epoch: [3][41/47],lr: 0.00005 Loss 1.6385 (2.0743) Prec@1 70.312 (62.290) Prec@5 92.188 (88.167)
Train Epoch: [3][47/47],lr: 0.00005 Loss 1.9536 (2.0375) Prec@1 64.151 (62.613) Prec@5 89.623 (88.505)
Val Epoch: [3][1/46] Loss 1.5821 (1.5821)
Cls@1:0.711 Cls@5:0.953
Loc@1:0.609 Loc@5:0.836 Loc_gt:0.883

Val Epoch: [3][11/46] Loss 1.4689 (1.5245)
Cls@1:0.670 Cls@5:0.915
Loc@1:0.572 Loc@5:0.788 Loc_gt:0.861

Val Epoch: [3][21/46] Loss 1.5379 (1.4357)
Cls@1:0.688 Cls@5:0.918
Loc@1:0.600 Loc@5:0.804 Loc_gt:0.873

Val Epoch: [3][31/46] Loss 1.9926 (1.5885)
Cls@1:0.654 Cls@5:0.898
Loc@1:0.566 Loc@5:0.779 Loc_gt:0.864

Val Epoch: [3][41/46] Loss 2.1024 (1.6257)
Cls@1:0.646 Cls@5:0.899
Loc@1:0.554 Loc@5:0.774 Loc_gt:0.855

Val Epoch: [3][46/46] Loss 1.3302 (1.5904)
Cls@1:0.659 Cls@5:0.904
Loc@1:0.566 Loc@5:0.778 Loc_gt:0.856

wrong_details:3282 1978 0 458 71 5
Best GT_LOC: 0.8555402140144978
Best TOP1_LOC: 0.8555402140144978
2021-09-07-19-32
Train Epoch: [4][1/47],lr: 0.00005 Loss 1.4536 (1.4536) Prec@1 73.438 (73.438) Prec@5 92.969 (92.969)
Train Epoch: [4][11/47],lr: 0.00005 Loss 1.5725 (1.4334) Prec@1 68.750 (75.497) Prec@5 93.750 (94.389)
Train Epoch: [4][21/47],lr: 0.00005 Loss 1.4201 (1.4106) Prec@1 75.781 (75.223) Prec@5 93.750 (94.382)
Train Epoch: [4][31/47],lr: 0.00005 Loss 1.2722 (1.3625) Prec@1 78.906 (75.781) Prec@5 96.094 (94.758)
Train Epoch: [4][41/47],lr: 0.00005 Loss 1.2769 (1.3315) Prec@1 72.656 (76.029) Prec@5 94.531 (95.084)
Train Epoch: [4][47/47],lr: 0.00005 Loss 1.2384 (1.3084) Prec@1 77.358 (76.243) Prec@5 95.283 (95.229)
Val Epoch: [4][1/46] Loss 1.2662 (1.2662)
Cls@1:0.773 Cls@5:0.938
Loc@1:0.656 Loc@5:0.820 Loc_gt:0.867

Val Epoch: [4][11/46] Loss 1.1712 (1.1959)
Cls@1:0.729 Cls@5:0.932
Loc@1:0.584 Loc@5:0.754 Loc_gt:0.804

Val Epoch: [4][21/46] Loss 1.1038 (1.1151)
Cls@1:0.748 Cls@5:0.935
Loc@1:0.621 Loc@5:0.781 Loc_gt:0.832

Val Epoch: [4][31/46] Loss 1.6659 (1.2428)
Cls@1:0.714 Cls@5:0.921
Loc@1:0.584 Loc@5:0.753 Loc_gt:0.815

Val Epoch: [4][41/46] Loss 1.5466 (1.2468)
Cls@1:0.715 Cls@5:0.924
Loc@1:0.575 Loc@5:0.746 Loc_gt:0.806

Val Epoch: [4][46/46] Loss 0.6745 (1.2114)
Cls@1:0.726 Cls@5:0.927
Loc@1:0.587 Loc@5:0.751 Loc_gt:0.808

wrong_details:3400 1585 0 745 61 3
Best GT_LOC: 0.8555402140144978
Best TOP1_LOC: 0.8555402140144978
2021-09-07-19-33
Train Epoch: [5][1/47],lr: 0.00005 Loss 0.9680 (0.9680) Prec@1 78.906 (78.906) Prec@5 99.219 (99.219)
Train Epoch: [5][11/47],lr: 0.00005 Loss 0.8547 (0.9744) Prec@1 85.938 (82.884) Prec@5 99.219 (97.727)
Train Epoch: [5][21/47],lr: 0.00005 Loss 1.0158 (0.9982) Prec@1 81.250 (81.659) Prec@5 96.094 (97.135)
Train Epoch: [5][31/47],lr: 0.00005 Loss 0.9685 (0.9808) Prec@1 82.812 (81.830) Prec@5 98.438 (97.253)
Train Epoch: [5][41/47],lr: 0.00005 Loss 0.9736 (0.9622) Prec@1 81.250 (82.298) Prec@5 94.531 (97.218)
Train Epoch: [5][47/47],lr: 0.00005 Loss 1.0469 (0.9540) Prec@1 75.472 (82.216) Prec@5 95.283 (97.130)
Val Epoch: [5][1/46] Loss 1.0615 (1.0615)
Cls@1:0.750 Cls@5:0.945
Loc@1:0.664 Loc@5:0.859 Loc_gt:0.906

Val Epoch: [5][11/46] Loss 0.8442 (1.0676)
Cls@1:0.720 Cls@5:0.928
Loc@1:0.616 Loc@5:0.798 Loc_gt:0.857

Val Epoch: [5][21/46] Loss 0.8507 (0.9830)
Cls@1:0.753 Cls@5:0.936
Loc@1:0.656 Loc@5:0.821 Loc_gt:0.872

Val Epoch: [5][31/46] Loss 1.3738 (1.0818)
Cls@1:0.736 Cls@5:0.926
Loc@1:0.637 Loc@5:0.804 Loc_gt:0.863

Val Epoch: [5][41/46] Loss 1.2694 (1.0753)
Cls@1:0.741 Cls@5:0.931
Loc@1:0.637 Loc@5:0.803 Loc_gt:0.856

Val Epoch: [5][46/46] Loss 0.6619 (1.0461)
Cls@1:0.751 Cls@5:0.934
Loc@1:0.647 Loc@5:0.806 Loc_gt:0.857

wrong_details:3746 1441 0 524 81 2
Best GT_LOC: 0.8570935450466
Best TOP1_LOC: 0.8570935450466
2021-09-07-19-34
Train Epoch: [6][1/47],lr: 0.00005 Loss 0.8027 (0.8027) Prec@1 87.500 (87.500) Prec@5 98.438 (98.438)
Train Epoch: [6][11/47],lr: 0.00005 Loss 0.7318 (0.7510) Prec@1 87.500 (87.287) Prec@5 97.656 (97.798)
Train Epoch: [6][21/47],lr: 0.00005 Loss 0.6998 (0.7218) Prec@1 86.719 (87.612) Prec@5 97.656 (97.954)
Train Epoch: [6][31/47],lr: 0.00005 Loss 0.6897 (0.7209) Prec@1 86.719 (87.349) Prec@5 98.438 (98.085)
Train Epoch: [6][41/47],lr: 0.00005 Loss 0.6273 (0.7195) Prec@1 90.625 (87.005) Prec@5 98.438 (98.056)
Train Epoch: [6][47/47],lr: 0.00005 Loss 0.6772 (0.7156) Prec@1 85.849 (86.854) Prec@5 99.057 (98.065)
Val Epoch: [6][1/46] Loss 1.0018 (1.0018)
Cls@1:0.781 Cls@5:0.945
Loc@1:0.680 Loc@5:0.844 Loc_gt:0.891

Val Epoch: [6][11/46] Loss 0.8060 (0.9390)
Cls@1:0.757 Cls@5:0.942
Loc@1:0.637 Loc@5:0.798 Loc_gt:0.845

Val Epoch: [6][21/46] Loss 0.8033 (0.8707)
Cls@1:0.780 Cls@5:0.947
Loc@1:0.674 Loc@5:0.824 Loc_gt:0.867

Val Epoch: [6][31/46] Loss 1.2483 (0.9782)
Cls@1:0.748 Cls@5:0.935
Loc@1:0.640 Loc@5:0.802 Loc_gt:0.854

Val Epoch: [6][41/46] Loss 1.0950 (0.9715)
Cls@1:0.747 Cls@5:0.939
Loc@1:0.632 Loc@5:0.798 Loc_gt:0.846

Val Epoch: [6][46/46] Loss 0.4847 (0.9405)
Cls@1:0.757 Cls@5:0.942
Loc@1:0.642 Loc@5:0.802 Loc_gt:0.848

wrong_details:3722 1410 0 587 73 2
Best GT_LOC: 0.8570935450466
Best TOP1_LOC: 0.8570935450466
2021-09-07-19-35
Train Epoch: [7][1/47],lr: 0.00005 Loss 0.6315 (0.6315) Prec@1 90.625 (90.625) Prec@5 98.438 (98.438)
Train Epoch: [7][11/47],lr: 0.00005 Loss 0.6201 (0.6014) Prec@1 92.188 (90.696) Prec@5 100.000 (99.006)
Train Epoch: [7][21/47],lr: 0.00005 Loss 0.4957 (0.5805) Prec@1 92.188 (90.699) Prec@5 98.438 (99.070)
Train Epoch: [7][31/47],lr: 0.00005 Loss 0.4101 (0.5792) Prec@1 92.969 (90.222) Prec@5 100.000 (99.093)
Train Epoch: [7][41/47],lr: 0.00005 Loss 0.5541 (0.5650) Prec@1 87.500 (90.282) Prec@5 99.219 (99.028)
Train Epoch: [7][47/47],lr: 0.00005 Loss 0.5090 (0.5652) Prec@1 93.396 (90.257) Prec@5 99.057 (98.999)
Val Epoch: [7][1/46] Loss 0.8949 (0.8949)
Cls@1:0.773 Cls@5:0.961
Loc@1:0.680 Loc@5:0.859 Loc_gt:0.891

Val Epoch: [7][11/46] Loss 0.7304 (0.8717)
Cls@1:0.755 Cls@5:0.946
Loc@1:0.620 Loc@5:0.784 Loc_gt:0.825

Val Epoch: [7][21/46] Loss 0.8041 (0.8207)
Cls@1:0.778 Cls@5:0.948
Loc@1:0.658 Loc@5:0.809 Loc_gt:0.851

Val Epoch: [7][31/46] Loss 1.3656 (0.9178)
Cls@1:0.756 Cls@5:0.938
Loc@1:0.633 Loc@5:0.790 Loc_gt:0.838

Val Epoch: [7][41/46] Loss 1.1323 (0.9031)
Cls@1:0.761 Cls@5:0.940
Loc@1:0.631 Loc@5:0.786 Loc_gt:0.831

Val Epoch: [7][46/46] Loss 0.3167 (0.8771)
Cls@1:0.770 Cls@5:0.942
Loc@1:0.639 Loc@5:0.788 Loc_gt:0.832

wrong_details:3705 1334 0 683 70 2
Best GT_LOC: 0.8570935450466
Best TOP1_LOC: 0.8570935450466
2021-09-07-19-36
Train Epoch: [8][1/47],lr: 0.00005 Loss 0.4352 (0.4352) Prec@1 92.188 (92.188) Prec@5 100.000 (100.000)
Train Epoch: [8][11/47],lr: 0.00005 Loss 0.5096 (0.4644) Prec@1 89.062 (91.974) Prec@5 99.219 (99.290)
Train Epoch: [8][21/47],lr: 0.00005 Loss 0.5946 (0.4626) Prec@1 89.844 (91.853) Prec@5 97.656 (99.368)
Train Epoch: [8][31/47],lr: 0.00005 Loss 0.4188 (0.4567) Prec@1 90.625 (91.683) Prec@5 100.000 (99.420)
Train Epoch: [8][41/47],lr: 0.00005 Loss 0.3957 (0.4591) Prec@1 92.969 (91.597) Prec@5 100.000 (99.333)
Train Epoch: [8][47/47],lr: 0.00005 Loss 0.4402 (0.4548) Prec@1 91.509 (91.608) Prec@5 99.057 (99.333)
Val Epoch: [8][1/46] Loss 0.8075 (0.8075)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.703 Loc@5:0.867 Loc_gt:0.891

Val Epoch: [8][11/46] Loss 0.6872 (0.8220)
Cls@1:0.769 Cls@5:0.950
Loc@1:0.638 Loc@5:0.787 Loc_gt:0.827

Val Epoch: [8][21/46] Loss 0.7409 (0.7763)
Cls@1:0.789 Cls@5:0.952
Loc@1:0.675 Loc@5:0.816 Loc_gt:0.855

Val Epoch: [8][31/46] Loss 1.2010 (0.8661)
Cls@1:0.768 Cls@5:0.943
Loc@1:0.649 Loc@5:0.797 Loc_gt:0.841

Val Epoch: [8][41/46] Loss 0.9893 (0.8564)
Cls@1:0.773 Cls@5:0.945
Loc@1:0.648 Loc@5:0.793 Loc_gt:0.835

Val Epoch: [8][46/46] Loss 0.3012 (0.8300)
Cls@1:0.782 Cls@5:0.947
Loc@1:0.656 Loc@5:0.795 Loc_gt:0.835

wrong_details:3798 1264 0 647 82 3
Best GT_LOC: 0.8570935450466
Best TOP1_LOC: 0.8570935450466
2021-09-07-19-37
Train Epoch: [9][1/47],lr: 0.00005 Loss 0.3146 (0.3146) Prec@1 91.406 (91.406) Prec@5 99.219 (99.219)
Train Epoch: [9][11/47],lr: 0.00005 Loss 0.3382 (0.3463) Prec@1 92.188 (94.815) Prec@5 100.000 (99.787)
Train Epoch: [9][21/47],lr: 0.00005 Loss 0.3892 (0.3638) Prec@1 94.531 (94.234) Prec@5 100.000 (99.702)
Train Epoch: [9][31/47],lr: 0.00005 Loss 0.4666 (0.3716) Prec@1 92.188 (94.103) Prec@5 99.219 (99.672)
Train Epoch: [9][41/47],lr: 0.00005 Loss 0.4284 (0.3656) Prec@1 92.188 (94.322) Prec@5 99.219 (99.657)
Train Epoch: [9][47/47],lr: 0.00005 Loss 0.4826 (0.3715) Prec@1 95.283 (94.194) Prec@5 99.057 (99.666)
Val Epoch: [9][1/46] Loss 0.8187 (0.8187)
Cls@1:0.773 Cls@5:0.961
Loc@1:0.695 Loc@5:0.875 Loc_gt:0.914

Val Epoch: [9][11/46] Loss 0.6245 (0.8147)
Cls@1:0.770 Cls@5:0.945
Loc@1:0.646 Loc@5:0.794 Loc_gt:0.837

Val Epoch: [9][21/46] Loss 0.6443 (0.7530)
Cls@1:0.794 Cls@5:0.951
Loc@1:0.685 Loc@5:0.821 Loc_gt:0.860

Val Epoch: [9][31/46] Loss 1.2618 (0.8612)
Cls@1:0.764 Cls@5:0.939
Loc@1:0.651 Loc@5:0.801 Loc_gt:0.848

Val Epoch: [9][41/46] Loss 0.9666 (0.8407)
Cls@1:0.772 Cls@5:0.943
Loc@1:0.649 Loc@5:0.796 Loc_gt:0.838

Val Epoch: [9][46/46] Loss 0.3046 (0.8129)
Cls@1:0.781 Cls@5:0.946
Loc@1:0.658 Loc@5:0.799 Loc_gt:0.839

wrong_details:3812 1270 0 626 83 3
Best GT_LOC: 0.8570935450466
Best TOP1_LOC: 0.8570935450466
2021-09-07-19-38
Train Epoch: [10][1/47],lr: 0.00005 Loss 0.2113 (0.2113) Prec@1 97.656 (97.656) Prec@5 100.000 (100.000)
Train Epoch: [10][11/47],lr: 0.00005 Loss 0.3710 (0.2738) Prec@1 92.188 (96.165) Prec@5 100.000 (99.929)
Train Epoch: [10][21/47],lr: 0.00005 Loss 0.2167 (0.2899) Prec@1 98.438 (95.499) Prec@5 100.000 (99.777)
Train Epoch: [10][31/47],lr: 0.00005 Loss 0.2903 (0.3022) Prec@1 96.094 (95.161) Prec@5 99.219 (99.773)
Train Epoch: [10][41/47],lr: 0.00005 Loss 0.3561 (0.3018) Prec@1 92.969 (94.970) Prec@5 100.000 (99.733)
Train Epoch: [10][47/47],lr: 0.00005 Loss 0.2733 (0.3074) Prec@1 96.226 (94.761) Prec@5 100.000 (99.750)
Val Epoch: [10][1/46] Loss 0.7915 (0.7915)
Cls@1:0.812 Cls@5:0.969
Loc@1:0.719 Loc@5:0.867 Loc_gt:0.883

Val Epoch: [10][11/46] Loss 0.7614 (0.8176)
Cls@1:0.767 Cls@5:0.947
Loc@1:0.653 Loc@5:0.812 Loc_gt:0.852

Val Epoch: [10][21/46] Loss 0.5936 (0.7414)
Cls@1:0.792 Cls@5:0.952
Loc@1:0.693 Loc@5:0.837 Loc_gt:0.875

Val Epoch: [10][31/46] Loss 1.2002 (0.8372)
Cls@1:0.768 Cls@5:0.941
Loc@1:0.669 Loc@5:0.822 Loc_gt:0.868

Val Epoch: [10][41/46] Loss 1.0969 (0.8292)
Cls@1:0.773 Cls@5:0.943
Loc@1:0.669 Loc@5:0.819 Loc_gt:0.862

Val Epoch: [10][46/46] Loss 0.4069 (0.8036)
Cls@1:0.782 Cls@5:0.945
Loc@1:0.678 Loc@5:0.822 Loc_gt:0.864

wrong_details:3930 1261 0 504 96 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-39
Train Epoch: [11][1/47],lr: 0.00005 Loss 0.2339 (0.2339) Prec@1 96.094 (96.094) Prec@5 100.000 (100.000)
Train Epoch: [11][11/47],lr: 0.00005 Loss 0.2475 (0.2511) Prec@1 94.531 (96.094) Prec@5 100.000 (99.858)
Train Epoch: [11][21/47],lr: 0.00005 Loss 0.2056 (0.2378) Prec@1 98.438 (96.466) Prec@5 100.000 (99.926)
Train Epoch: [11][31/47],lr: 0.00005 Loss 0.2072 (0.2428) Prec@1 96.094 (96.396) Prec@5 100.000 (99.899)
Train Epoch: [11][41/47],lr: 0.00005 Loss 0.1670 (0.2407) Prec@1 98.438 (96.380) Prec@5 100.000 (99.924)
Train Epoch: [11][47/47],lr: 0.00005 Loss 0.2610 (0.2434) Prec@1 96.226 (96.296) Prec@5 100.000 (99.900)
Val Epoch: [11][1/46] Loss 0.7770 (0.7770)
Cls@1:0.789 Cls@5:0.969
Loc@1:0.711 Loc@5:0.883 Loc_gt:0.898

Val Epoch: [11][11/46] Loss 0.6289 (0.7831)
Cls@1:0.774 Cls@5:0.947
Loc@1:0.641 Loc@5:0.790 Loc_gt:0.830

Val Epoch: [11][21/46] Loss 0.6238 (0.7262)
Cls@1:0.795 Cls@5:0.951
Loc@1:0.679 Loc@5:0.818 Loc_gt:0.857

Val Epoch: [11][31/46] Loss 1.1892 (0.8241)
Cls@1:0.775 Cls@5:0.940
Loc@1:0.651 Loc@5:0.796 Loc_gt:0.842

Val Epoch: [11][41/46] Loss 1.0390 (0.8132)
Cls@1:0.781 Cls@5:0.943
Loc@1:0.652 Loc@5:0.794 Loc_gt:0.837

Val Epoch: [11][46/46] Loss 0.2945 (0.7853)
Cls@1:0.791 Cls@5:0.945
Loc@1:0.661 Loc@5:0.797 Loc_gt:0.838

wrong_details:3829 1213 0 665 84 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-40
Train Epoch: [12][1/47],lr: 0.00005 Loss 0.2822 (0.2822) Prec@1 96.875 (96.875) Prec@5 100.000 (100.000)
Train Epoch: [12][11/47],lr: 0.00005 Loss 0.1636 (0.1938) Prec@1 100.000 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [12][21/47],lr: 0.00005 Loss 0.2105 (0.2050) Prec@1 95.312 (97.656) Prec@5 100.000 (99.963)
Train Epoch: [12][31/47],lr: 0.00005 Loss 0.2924 (0.2075) Prec@1 94.531 (97.606) Prec@5 100.000 (99.950)
Train Epoch: [12][41/47],lr: 0.00005 Loss 0.1464 (0.2056) Prec@1 96.875 (97.523) Prec@5 100.000 (99.905)
Train Epoch: [12][47/47],lr: 0.00005 Loss 0.2949 (0.2077) Prec@1 99.057 (97.514) Prec@5 99.057 (99.883)
Val Epoch: [12][1/46] Loss 0.7195 (0.7195)
Cls@1:0.820 Cls@5:0.961
Loc@1:0.758 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [12][11/46] Loss 0.6377 (0.7733)
Cls@1:0.780 Cls@5:0.951
Loc@1:0.664 Loc@5:0.813 Loc_gt:0.852

Val Epoch: [12][21/46] Loss 0.7180 (0.7362)
Cls@1:0.795 Cls@5:0.951
Loc@1:0.697 Loc@5:0.835 Loc_gt:0.876

Val Epoch: [12][31/46] Loss 1.2625 (0.8315)
Cls@1:0.773 Cls@5:0.940
Loc@1:0.670 Loc@5:0.816 Loc_gt:0.864

Val Epoch: [12][41/46] Loss 0.9469 (0.8163)
Cls@1:0.777 Cls@5:0.942
Loc@1:0.669 Loc@5:0.813 Loc_gt:0.858

Val Epoch: [12][46/46] Loss 0.3243 (0.7890)
Cls@1:0.785 Cls@5:0.944
Loc@1:0.675 Loc@5:0.814 Loc_gt:0.857

wrong_details:3909 1248 0 539 93 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-41
Train Epoch: [13][1/47],lr: 0.00005 Loss 0.2026 (0.2026) Prec@1 96.875 (96.875) Prec@5 100.000 (100.000)
Train Epoch: [13][11/47],lr: 0.00005 Loss 0.1435 (0.1634) Prec@1 99.219 (98.295) Prec@5 100.000 (100.000)
Train Epoch: [13][21/47],lr: 0.00005 Loss 0.1863 (0.1672) Prec@1 99.219 (97.842) Prec@5 100.000 (100.000)
Train Epoch: [13][31/47],lr: 0.00005 Loss 0.1605 (0.1721) Prec@1 98.438 (97.782) Prec@5 100.000 (100.000)
Train Epoch: [13][41/47],lr: 0.00005 Loss 0.1677 (0.1741) Prec@1 98.438 (97.771) Prec@5 100.000 (99.981)
Train Epoch: [13][47/47],lr: 0.00005 Loss 0.2207 (0.1728) Prec@1 98.113 (97.814) Prec@5 100.000 (99.967)
Val Epoch: [13][1/46] Loss 0.6704 (0.6704)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.906

Val Epoch: [13][11/46] Loss 0.5995 (0.7934)
Cls@1:0.778 Cls@5:0.947
Loc@1:0.658 Loc@5:0.802 Loc_gt:0.844

Val Epoch: [13][21/46] Loss 0.6599 (0.7346)
Cls@1:0.798 Cls@5:0.951
Loc@1:0.692 Loc@5:0.827 Loc_gt:0.868

Val Epoch: [13][31/46] Loss 1.0626 (0.8288)
Cls@1:0.779 Cls@5:0.940
Loc@1:0.667 Loc@5:0.807 Loc_gt:0.854

Val Epoch: [13][41/46] Loss 0.9556 (0.8126)
Cls@1:0.785 Cls@5:0.943
Loc@1:0.667 Loc@5:0.804 Loc_gt:0.848

Val Epoch: [13][46/46] Loss 0.2010 (0.7830)
Cls@1:0.794 Cls@5:0.945
Loc@1:0.674 Loc@5:0.807 Loc_gt:0.849

wrong_details:3908 1195 0 615 72 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-42
Train Epoch: [14][1/47],lr: 0.00005 Loss 0.1383 (0.1383) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [14][11/47],lr: 0.00005 Loss 0.2603 (0.1449) Prec@1 96.875 (98.366) Prec@5 100.000 (100.000)
Train Epoch: [14][21/47],lr: 0.00005 Loss 0.1428 (0.1561) Prec@1 98.438 (98.028) Prec@5 100.000 (100.000)
Train Epoch: [14][31/47],lr: 0.00005 Loss 0.1001 (0.1545) Prec@1 100.000 (98.110) Prec@5 100.000 (99.975)
Train Epoch: [14][41/47],lr: 0.00005 Loss 0.1319 (0.1539) Prec@1 100.000 (98.075) Prec@5 100.000 (99.962)
Train Epoch: [14][47/47],lr: 0.00005 Loss 0.1216 (0.1519) Prec@1 97.170 (98.098) Prec@5 100.000 (99.967)
Val Epoch: [14][1/46] Loss 0.7077 (0.7077)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.711 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [14][11/46] Loss 0.7107 (0.7861)
Cls@1:0.780 Cls@5:0.950
Loc@1:0.655 Loc@5:0.799 Loc_gt:0.840

Val Epoch: [14][21/46] Loss 0.6405 (0.7272)
Cls@1:0.804 Cls@5:0.951
Loc@1:0.695 Loc@5:0.824 Loc_gt:0.865

Val Epoch: [14][31/46] Loss 1.1478 (0.8288)
Cls@1:0.781 Cls@5:0.941
Loc@1:0.670 Loc@5:0.807 Loc_gt:0.854

Val Epoch: [14][41/46] Loss 0.9925 (0.8117)
Cls@1:0.786 Cls@5:0.944
Loc@1:0.672 Loc@5:0.807 Loc_gt:0.850

Val Epoch: [14][46/46] Loss 0.1437 (0.7837)
Cls@1:0.795 Cls@5:0.946
Loc@1:0.678 Loc@5:0.808 Loc_gt:0.850

wrong_details:3929 1189 0 570 101 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-43
Train Epoch: [15][1/47],lr: 0.00005 Loss 0.0953 (0.0953) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [15][11/47],lr: 0.00005 Loss 0.1292 (0.1253) Prec@1 98.438 (98.651) Prec@5 100.000 (99.929)
Train Epoch: [15][21/47],lr: 0.00005 Loss 0.1509 (0.1300) Prec@1 99.219 (98.512) Prec@5 99.219 (99.888)
Train Epoch: [15][31/47],lr: 0.00005 Loss 0.1539 (0.1270) Prec@1 96.875 (98.438) Prec@5 99.219 (99.899)
Train Epoch: [15][41/47],lr: 0.00005 Loss 0.1715 (0.1332) Prec@1 97.656 (98.361) Prec@5 100.000 (99.905)
Train Epoch: [15][47/47],lr: 0.00005 Loss 0.0793 (0.1295) Prec@1 99.057 (98.448) Prec@5 100.000 (99.917)
Val Epoch: [15][1/46] Loss 0.6943 (0.6943)
Cls@1:0.812 Cls@5:0.961
Loc@1:0.727 Loc@5:0.867 Loc_gt:0.898

Val Epoch: [15][11/46] Loss 0.6468 (0.7621)
Cls@1:0.793 Cls@5:0.950
Loc@1:0.654 Loc@5:0.788 Loc_gt:0.827

Val Epoch: [15][21/46] Loss 0.6859 (0.7303)
Cls@1:0.804 Cls@5:0.951
Loc@1:0.683 Loc@5:0.810 Loc_gt:0.849

Val Epoch: [15][31/46] Loss 1.1717 (0.8322)
Cls@1:0.780 Cls@5:0.939
Loc@1:0.657 Loc@5:0.790 Loc_gt:0.835

Val Epoch: [15][41/46] Loss 0.8882 (0.8147)
Cls@1:0.784 Cls@5:0.942
Loc@1:0.654 Loc@5:0.787 Loc_gt:0.830

Val Epoch: [15][46/46] Loss 0.2022 (0.7873)
Cls@1:0.792 Cls@5:0.944
Loc@1:0.661 Loc@5:0.789 Loc_gt:0.831

wrong_details:3828 1207 0 670 86 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-44
Train Epoch: [16][1/47],lr: 0.00005 Loss 0.0766 (0.0766) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [16][11/47],lr: 0.00005 Loss 0.1435 (0.1288) Prec@1 98.438 (99.148) Prec@5 100.000 (99.929)
Train Epoch: [16][21/47],lr: 0.00005 Loss 0.1793 (0.1191) Prec@1 98.438 (99.070) Prec@5 100.000 (99.963)
Train Epoch: [16][31/47],lr: 0.00005 Loss 0.1648 (0.1189) Prec@1 98.438 (98.891) Prec@5 99.219 (99.950)
Train Epoch: [16][41/47],lr: 0.00005 Loss 0.1340 (0.1176) Prec@1 99.219 (98.800) Prec@5 100.000 (99.962)
Train Epoch: [16][47/47],lr: 0.00005 Loss 0.0883 (0.1193) Prec@1 98.113 (98.732) Prec@5 100.000 (99.967)
Val Epoch: [16][1/46] Loss 0.7034 (0.7034)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.766 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [16][11/46] Loss 0.6337 (0.7903)
Cls@1:0.784 Cls@5:0.953
Loc@1:0.671 Loc@5:0.816 Loc_gt:0.854

Val Epoch: [16][21/46] Loss 0.6130 (0.7391)
Cls@1:0.801 Cls@5:0.952
Loc@1:0.699 Loc@5:0.833 Loc_gt:0.872

Val Epoch: [16][31/46] Loss 1.1771 (0.8350)
Cls@1:0.780 Cls@5:0.941
Loc@1:0.678 Loc@5:0.817 Loc_gt:0.863

Val Epoch: [16][41/46] Loss 1.0027 (0.8242)
Cls@1:0.786 Cls@5:0.942
Loc@1:0.677 Loc@5:0.811 Loc_gt:0.856

Val Epoch: [16][46/46] Loss 0.2066 (0.7962)
Cls@1:0.794 Cls@5:0.943
Loc@1:0.683 Loc@5:0.812 Loc_gt:0.856

wrong_details:3957 1193 0 551 90 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-45
Train Epoch: [17][1/47],lr: 0.00005 Loss 0.0933 (0.0933) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [17][11/47],lr: 0.00005 Loss 0.1268 (0.1036) Prec@1 96.875 (98.295) Prec@5 100.000 (99.929)
Train Epoch: [17][21/47],lr: 0.00005 Loss 0.1248 (0.1019) Prec@1 98.438 (98.810) Prec@5 100.000 (99.963)
Train Epoch: [17][31/47],lr: 0.00005 Loss 0.1080 (0.0989) Prec@1 100.000 (98.891) Prec@5 100.000 (99.975)
Train Epoch: [17][41/47],lr: 0.00005 Loss 0.1242 (0.0982) Prec@1 98.438 (99.047) Prec@5 100.000 (99.981)
Train Epoch: [17][47/47],lr: 0.00005 Loss 0.1096 (0.0993) Prec@1 99.057 (99.132) Prec@5 100.000 (99.967)
Val Epoch: [17][1/46] Loss 0.7038 (0.7038)
Cls@1:0.789 Cls@5:0.969
Loc@1:0.719 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [17][11/46] Loss 0.6138 (0.7726)
Cls@1:0.784 Cls@5:0.962
Loc@1:0.660 Loc@5:0.812 Loc_gt:0.842

Val Epoch: [17][21/46] Loss 0.5834 (0.7203)
Cls@1:0.802 Cls@5:0.957
Loc@1:0.692 Loc@5:0.827 Loc_gt:0.864

Val Epoch: [17][31/46] Loss 1.1546 (0.8310)
Cls@1:0.780 Cls@5:0.943
Loc@1:0.668 Loc@5:0.808 Loc_gt:0.853

Val Epoch: [17][41/46] Loss 0.9620 (0.8149)
Cls@1:0.787 Cls@5:0.945
Loc@1:0.667 Loc@5:0.803 Loc_gt:0.845

Val Epoch: [17][46/46] Loss 0.2371 (0.7873)
Cls@1:0.793 Cls@5:0.947
Loc@1:0.673 Loc@5:0.805 Loc_gt:0.845

wrong_details:3898 1200 0 600 92 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-46
Train Epoch: [18][1/47],lr: 0.00005 Loss 0.0652 (0.0652) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [18][11/47],lr: 0.00005 Loss 0.1210 (0.1097) Prec@1 98.438 (98.509) Prec@5 100.000 (100.000)
Train Epoch: [18][21/47],lr: 0.00005 Loss 0.0984 (0.1068) Prec@1 100.000 (98.996) Prec@5 100.000 (100.000)
Train Epoch: [18][31/47],lr: 0.00005 Loss 0.0777 (0.1011) Prec@1 100.000 (99.194) Prec@5 100.000 (100.000)
Train Epoch: [18][41/47],lr: 0.00005 Loss 0.0838 (0.1011) Prec@1 98.438 (99.200) Prec@5 100.000 (100.000)
Train Epoch: [18][47/47],lr: 0.00005 Loss 0.0942 (0.1019) Prec@1 100.000 (99.249) Prec@5 100.000 (100.000)
Val Epoch: [18][1/46] Loss 0.6567 (0.6567)
Cls@1:0.820 Cls@5:0.961
Loc@1:0.742 Loc@5:0.883 Loc_gt:0.914

Val Epoch: [18][11/46] Loss 0.7361 (0.7885)
Cls@1:0.783 Cls@5:0.951
Loc@1:0.669 Loc@5:0.810 Loc_gt:0.846

Val Epoch: [18][21/46] Loss 0.5334 (0.7289)
Cls@1:0.803 Cls@5:0.952
Loc@1:0.703 Loc@5:0.832 Loc_gt:0.869

Val Epoch: [18][31/46] Loss 1.1724 (0.8370)
Cls@1:0.782 Cls@5:0.939
Loc@1:0.681 Loc@5:0.817 Loc_gt:0.863

Val Epoch: [18][41/46] Loss 0.9601 (0.8191)
Cls@1:0.787 Cls@5:0.942
Loc@1:0.680 Loc@5:0.814 Loc_gt:0.858

Val Epoch: [18][46/46] Loss 0.2828 (0.7910)
Cls@1:0.794 Cls@5:0.944
Loc@1:0.686 Loc@5:0.815 Loc_gt:0.858

wrong_details:3973 1191 0 511 115 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-47
Train Epoch: [19][1/47],lr: 0.00005 Loss 0.0829 (0.0829) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [19][11/47],lr: 0.00005 Loss 0.1072 (0.0782) Prec@1 99.219 (99.503) Prec@5 100.000 (100.000)
Train Epoch: [19][21/47],lr: 0.00005 Loss 0.0543 (0.0767) Prec@1 99.219 (99.479) Prec@5 100.000 (100.000)
Train Epoch: [19][31/47],lr: 0.00005 Loss 0.0796 (0.0737) Prec@1 99.219 (99.496) Prec@5 100.000 (100.000)
Train Epoch: [19][41/47],lr: 0.00005 Loss 0.0496 (0.0734) Prec@1 100.000 (99.543) Prec@5 100.000 (100.000)
Train Epoch: [19][47/47],lr: 0.00005 Loss 0.0655 (0.0747) Prec@1 99.057 (99.433) Prec@5 100.000 (100.000)
Val Epoch: [19][1/46] Loss 0.6045 (0.6045)
Cls@1:0.836 Cls@5:0.977
Loc@1:0.742 Loc@5:0.883 Loc_gt:0.898

Val Epoch: [19][11/46] Loss 0.7044 (0.7556)
Cls@1:0.792 Cls@5:0.957
Loc@1:0.662 Loc@5:0.797 Loc_gt:0.832

Val Epoch: [19][21/46] Loss 0.6124 (0.7185)
Cls@1:0.808 Cls@5:0.955
Loc@1:0.697 Loc@5:0.821 Loc_gt:0.859

Val Epoch: [19][31/46] Loss 1.0886 (0.8250)
Cls@1:0.787 Cls@5:0.941
Loc@1:0.673 Loc@5:0.800 Loc_gt:0.847

Val Epoch: [19][41/46] Loss 0.9525 (0.8140)
Cls@1:0.792 Cls@5:0.944
Loc@1:0.672 Loc@5:0.800 Loc_gt:0.843

Val Epoch: [19][46/46] Loss 0.2557 (0.7878)
Cls@1:0.799 Cls@5:0.945
Loc@1:0.677 Loc@5:0.800 Loc_gt:0.842

wrong_details:3923 1167 0 607 91 6
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-48
Train Epoch: [20][1/47],lr: 0.00005 Loss 0.0581 (0.0581) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [20][11/47],lr: 0.00005 Loss 0.0680 (0.0778) Prec@1 100.000 (99.361) Prec@5 100.000 (100.000)
Train Epoch: [20][21/47],lr: 0.00005 Loss 0.1008 (0.0746) Prec@1 98.438 (99.330) Prec@5 100.000 (99.963)
Train Epoch: [20][31/47],lr: 0.00005 Loss 0.0852 (0.0770) Prec@1 100.000 (99.294) Prec@5 100.000 (99.975)
Train Epoch: [20][41/47],lr: 0.00005 Loss 0.0908 (0.0765) Prec@1 100.000 (99.295) Prec@5 100.000 (99.981)
Train Epoch: [20][47/47],lr: 0.00005 Loss 0.0823 (0.0761) Prec@1 98.113 (99.283) Prec@5 100.000 (99.983)
Val Epoch: [20][1/46] Loss 0.6379 (0.6379)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.711 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [20][11/46] Loss 0.7418 (0.7872)
Cls@1:0.786 Cls@5:0.948
Loc@1:0.662 Loc@5:0.798 Loc_gt:0.836

Val Epoch: [20][21/46] Loss 0.5617 (0.7274)
Cls@1:0.804 Cls@5:0.952
Loc@1:0.698 Loc@5:0.826 Loc_gt:0.865

Val Epoch: [20][31/46] Loss 1.1347 (0.8307)
Cls@1:0.785 Cls@5:0.939
Loc@1:0.678 Loc@5:0.808 Loc_gt:0.856

Val Epoch: [20][41/46] Loss 0.8883 (0.8206)
Cls@1:0.792 Cls@5:0.941
Loc@1:0.678 Loc@5:0.806 Loc_gt:0.850

Val Epoch: [20][46/46] Loss 0.1533 (0.7923)
Cls@1:0.799 Cls@5:0.943
Loc@1:0.684 Loc@5:0.807 Loc_gt:0.850

wrong_details:3961 1164 0 563 101 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-49
Train Epoch: [21][1/47],lr: 0.00005 Loss 0.0635 (0.0635) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [21][11/47],lr: 0.00005 Loss 0.0480 (0.0607) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [21][21/47],lr: 0.00005 Loss 0.0746 (0.0588) Prec@1 99.219 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [21][31/47],lr: 0.00005 Loss 0.0500 (0.0626) Prec@1 100.000 (99.622) Prec@5 100.000 (100.000)
Train Epoch: [21][41/47],lr: 0.00005 Loss 0.0689 (0.0633) Prec@1 98.438 (99.562) Prec@5 100.000 (100.000)
Train Epoch: [21][47/47],lr: 0.00005 Loss 0.0784 (0.0638) Prec@1 99.057 (99.566) Prec@5 100.000 (100.000)
Val Epoch: [21][1/46] Loss 0.6954 (0.6954)
Cls@1:0.805 Cls@5:0.961
Loc@1:0.727 Loc@5:0.883 Loc_gt:0.922

Val Epoch: [21][11/46] Loss 0.6462 (0.8140)
Cls@1:0.790 Cls@5:0.949
Loc@1:0.671 Loc@5:0.803 Loc_gt:0.845

Val Epoch: [21][21/46] Loss 0.5362 (0.7449)
Cls@1:0.806 Cls@5:0.951
Loc@1:0.702 Loc@5:0.826 Loc_gt:0.869

Val Epoch: [21][31/46] Loss 1.1657 (0.8276)
Cls@1:0.791 Cls@5:0.941
Loc@1:0.684 Loc@5:0.812 Loc_gt:0.861

Val Epoch: [21][41/46] Loss 1.0326 (0.8137)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.684 Loc@5:0.810 Loc_gt:0.855

Val Epoch: [21][46/46] Loss 0.2299 (0.7881)
Cls@1:0.802 Cls@5:0.945
Loc@1:0.688 Loc@5:0.812 Loc_gt:0.855

wrong_details:3987 1146 0 554 102 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-50
Train Epoch: [22][1/47],lr: 0.00005 Loss 0.0448 (0.0448) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [22][11/47],lr: 0.00005 Loss 0.0486 (0.0544) Prec@1 100.000 (99.574) Prec@5 100.000 (100.000)
Train Epoch: [22][21/47],lr: 0.00005 Loss 0.0955 (0.0567) Prec@1 100.000 (99.665) Prec@5 100.000 (99.963)
Train Epoch: [22][31/47],lr: 0.00005 Loss 0.0395 (0.0573) Prec@1 99.219 (99.622) Prec@5 100.000 (99.975)
Train Epoch: [22][41/47],lr: 0.00005 Loss 0.0290 (0.0606) Prec@1 100.000 (99.505) Prec@5 100.000 (99.981)
Train Epoch: [22][47/47],lr: 0.00005 Loss 0.0545 (0.0597) Prec@1 100.000 (99.550) Prec@5 100.000 (99.983)
Val Epoch: [22][1/46] Loss 0.6252 (0.6252)
Cls@1:0.836 Cls@5:0.969
Loc@1:0.742 Loc@5:0.867 Loc_gt:0.891

Val Epoch: [22][11/46] Loss 0.6149 (0.7934)
Cls@1:0.786 Cls@5:0.953
Loc@1:0.665 Loc@5:0.810 Loc_gt:0.847

Val Epoch: [22][21/46] Loss 0.5432 (0.7333)
Cls@1:0.806 Cls@5:0.956
Loc@1:0.701 Loc@5:0.833 Loc_gt:0.869

Val Epoch: [22][31/46] Loss 1.1346 (0.8314)
Cls@1:0.786 Cls@5:0.946
Loc@1:0.676 Loc@5:0.812 Loc_gt:0.856

Val Epoch: [22][41/46] Loss 0.9682 (0.8206)
Cls@1:0.791 Cls@5:0.947
Loc@1:0.676 Loc@5:0.810 Loc_gt:0.851

Val Epoch: [22][46/46] Loss 0.1948 (0.7924)
Cls@1:0.798 Cls@5:0.949
Loc@1:0.682 Loc@5:0.811 Loc_gt:0.851

wrong_details:3950 1168 0 581 93 2
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-51
Train Epoch: [23][1/47],lr: 0.00005 Loss 0.0331 (0.0331) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [23][11/47],lr: 0.00005 Loss 0.0383 (0.0567) Prec@1 99.219 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [23][21/47],lr: 0.00005 Loss 0.0676 (0.0675) Prec@1 99.219 (99.330) Prec@5 100.000 (99.963)
Train Epoch: [23][31/47],lr: 0.00005 Loss 0.0838 (0.0634) Prec@1 98.438 (99.345) Prec@5 100.000 (99.975)
Train Epoch: [23][41/47],lr: 0.00005 Loss 0.0427 (0.0603) Prec@1 100.000 (99.409) Prec@5 100.000 (99.981)
Train Epoch: [23][47/47],lr: 0.00005 Loss 0.0520 (0.0600) Prec@1 99.057 (99.399) Prec@5 100.000 (99.983)
Val Epoch: [23][1/46] Loss 0.6621 (0.6621)
Cls@1:0.812 Cls@5:0.961
Loc@1:0.734 Loc@5:0.883 Loc_gt:0.914

Val Epoch: [23][11/46] Loss 0.6482 (0.8013)
Cls@1:0.787 Cls@5:0.944
Loc@1:0.665 Loc@5:0.801 Loc_gt:0.847

Val Epoch: [23][21/46] Loss 0.5643 (0.7390)
Cls@1:0.806 Cls@5:0.948
Loc@1:0.702 Loc@5:0.825 Loc_gt:0.869

Val Epoch: [23][31/46] Loss 1.1637 (0.8354)
Cls@1:0.788 Cls@5:0.938
Loc@1:0.675 Loc@5:0.803 Loc_gt:0.854

Val Epoch: [23][41/46] Loss 1.0419 (0.8255)
Cls@1:0.793 Cls@5:0.941
Loc@1:0.676 Loc@5:0.803 Loc_gt:0.849

Val Epoch: [23][46/46] Loss 0.1833 (0.7957)
Cls@1:0.801 Cls@5:0.943
Loc@1:0.682 Loc@5:0.805 Loc_gt:0.849

wrong_details:3954 1154 0 584 99 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-52
Train Epoch: [24][1/47],lr: 0.00005 Loss 0.0494 (0.0494) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [24][11/47],lr: 0.00005 Loss 0.0376 (0.0593) Prec@1 99.219 (99.503) Prec@5 100.000 (100.000)
Train Epoch: [24][21/47],lr: 0.00005 Loss 0.0188 (0.0526) Prec@1 100.000 (99.554) Prec@5 100.000 (100.000)
Train Epoch: [24][31/47],lr: 0.00005 Loss 0.0290 (0.0472) Prec@1 100.000 (99.597) Prec@5 100.000 (100.000)
Train Epoch: [24][41/47],lr: 0.00005 Loss 0.0506 (0.0466) Prec@1 100.000 (99.600) Prec@5 100.000 (99.981)
Train Epoch: [24][47/47],lr: 0.00005 Loss 0.0378 (0.0451) Prec@1 99.057 (99.600) Prec@5 100.000 (99.983)
Val Epoch: [24][1/46] Loss 0.6482 (0.6482)
Cls@1:0.812 Cls@5:0.977
Loc@1:0.727 Loc@5:0.891 Loc_gt:0.906

Val Epoch: [24][11/46] Loss 0.6865 (0.7883)
Cls@1:0.791 Cls@5:0.951
Loc@1:0.662 Loc@5:0.798 Loc_gt:0.839

Val Epoch: [24][21/46] Loss 0.5503 (0.7353)
Cls@1:0.808 Cls@5:0.953
Loc@1:0.697 Loc@5:0.823 Loc_gt:0.863

Val Epoch: [24][31/46] Loss 1.1485 (0.8364)
Cls@1:0.788 Cls@5:0.942
Loc@1:0.671 Loc@5:0.802 Loc_gt:0.849

Val Epoch: [24][41/46] Loss 1.0229 (0.8256)
Cls@1:0.790 Cls@5:0.943
Loc@1:0.668 Loc@5:0.800 Loc_gt:0.843

Val Epoch: [24][46/46] Loss 0.1761 (0.7954)
Cls@1:0.798 Cls@5:0.946
Loc@1:0.674 Loc@5:0.801 Loc_gt:0.843

wrong_details:3903 1168 0 620 99 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-53
Train Epoch: [25][1/47],lr: 0.00005 Loss 0.0281 (0.0281) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [25][11/47],lr: 0.00005 Loss 0.0488 (0.0445) Prec@1 100.000 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [25][21/47],lr: 0.00005 Loss 0.0521 (0.0444) Prec@1 99.219 (99.591) Prec@5 100.000 (100.000)
Train Epoch: [25][31/47],lr: 0.00005 Loss 0.0640 (0.0477) Prec@1 98.438 (99.521) Prec@5 100.000 (100.000)
Train Epoch: [25][41/47],lr: 0.00005 Loss 0.0414 (0.0464) Prec@1 100.000 (99.562) Prec@5 100.000 (100.000)
Train Epoch: [25][47/47],lr: 0.00005 Loss 0.0336 (0.0475) Prec@1 100.000 (99.550) Prec@5 100.000 (100.000)
Val Epoch: [25][1/46] Loss 0.6883 (0.6883)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.750 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [25][11/46] Loss 0.6368 (0.8144)
Cls@1:0.782 Cls@5:0.955
Loc@1:0.669 Loc@5:0.820 Loc_gt:0.856

Val Epoch: [25][21/46] Loss 0.5522 (0.7534)
Cls@1:0.804 Cls@5:0.954
Loc@1:0.705 Loc@5:0.839 Loc_gt:0.877

Val Epoch: [25][31/46] Loss 1.2875 (0.8550)
Cls@1:0.786 Cls@5:0.942
Loc@1:0.685 Loc@5:0.821 Loc_gt:0.868

Val Epoch: [25][41/46] Loss 1.0226 (0.8365)
Cls@1:0.792 Cls@5:0.945
Loc@1:0.686 Loc@5:0.818 Loc_gt:0.861

Val Epoch: [25][46/46] Loss 0.2162 (0.8073)
Cls@1:0.800 Cls@5:0.946
Loc@1:0.692 Loc@5:0.819 Loc_gt:0.862

wrong_details:4011 1157 0 526 95 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-54
Train Epoch: [26][1/47],lr: 0.00005 Loss 0.0395 (0.0395) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [26][11/47],lr: 0.00005 Loss 0.0393 (0.0452) Prec@1 100.000 (99.503) Prec@5 100.000 (100.000)
Train Epoch: [26][21/47],lr: 0.00005 Loss 0.0769 (0.0485) Prec@1 99.219 (99.516) Prec@5 99.219 (99.926)
Train Epoch: [26][31/47],lr: 0.00005 Loss 0.0387 (0.0510) Prec@1 100.000 (99.546) Prec@5 100.000 (99.950)
Train Epoch: [26][41/47],lr: 0.00005 Loss 0.0265 (0.0468) Prec@1 100.000 (99.619) Prec@5 100.000 (99.962)
Train Epoch: [26][47/47],lr: 0.00005 Loss 0.0400 (0.0470) Prec@1 100.000 (99.633) Prec@5 100.000 (99.967)
Val Epoch: [26][1/46] Loss 0.7217 (0.7217)
Cls@1:0.805 Cls@5:0.961
Loc@1:0.734 Loc@5:0.891 Loc_gt:0.930

Val Epoch: [26][11/46] Loss 0.6378 (0.8169)
Cls@1:0.786 Cls@5:0.952
Loc@1:0.663 Loc@5:0.801 Loc_gt:0.844

Val Epoch: [26][21/46] Loss 0.6628 (0.7649)
Cls@1:0.804 Cls@5:0.952
Loc@1:0.695 Loc@5:0.822 Loc_gt:0.863

Val Epoch: [26][31/46] Loss 1.1647 (0.8580)
Cls@1:0.786 Cls@5:0.942
Loc@1:0.674 Loc@5:0.805 Loc_gt:0.852

Val Epoch: [26][41/46] Loss 1.0255 (0.8478)
Cls@1:0.790 Cls@5:0.944
Loc@1:0.674 Loc@5:0.804 Loc_gt:0.847

Val Epoch: [26][46/46] Loss 0.1758 (0.8180)
Cls@1:0.798 Cls@5:0.946
Loc@1:0.682 Loc@5:0.807 Loc_gt:0.848

wrong_details:3949 1170 0 563 107 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-55
Train Epoch: [27][1/47],lr: 0.00005 Loss 0.0329 (0.0329) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [27][11/47],lr: 0.00005 Loss 0.0293 (0.0481) Prec@1 100.000 (99.645) Prec@5 100.000 (99.858)
Train Epoch: [27][21/47],lr: 0.00005 Loss 0.0632 (0.0464) Prec@1 98.438 (99.591) Prec@5 100.000 (99.926)
Train Epoch: [27][31/47],lr: 0.00005 Loss 0.0266 (0.0423) Prec@1 100.000 (99.647) Prec@5 100.000 (99.950)
Train Epoch: [27][41/47],lr: 0.00005 Loss 0.0792 (0.0433) Prec@1 99.219 (99.676) Prec@5 99.219 (99.943)
Train Epoch: [27][47/47],lr: 0.00005 Loss 0.0314 (0.0426) Prec@1 100.000 (99.666) Prec@5 100.000 (99.950)
Val Epoch: [27][1/46] Loss 0.7177 (0.7177)
Cls@1:0.789 Cls@5:0.953
Loc@1:0.688 Loc@5:0.852 Loc_gt:0.898

Val Epoch: [27][11/46] Loss 0.6447 (0.8491)
Cls@1:0.778 Cls@5:0.945
Loc@1:0.650 Loc@5:0.795 Loc_gt:0.844

Val Epoch: [27][21/46] Loss 0.5949 (0.7790)
Cls@1:0.798 Cls@5:0.949
Loc@1:0.689 Loc@5:0.821 Loc_gt:0.865

Val Epoch: [27][31/46] Loss 1.1569 (0.8648)
Cls@1:0.782 Cls@5:0.939
Loc@1:0.669 Loc@5:0.803 Loc_gt:0.854

Val Epoch: [27][41/46] Loss 1.0440 (0.8488)
Cls@1:0.789 Cls@5:0.942
Loc@1:0.673 Loc@5:0.804 Loc_gt:0.849

Val Epoch: [27][46/46] Loss 0.1530 (0.8205)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.680 Loc@5:0.806 Loc_gt:0.850

wrong_details:3942 1175 0 576 97 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-56
Train Epoch: [28][1/47],lr: 0.00005 Loss 0.0340 (0.0340) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [28][11/47],lr: 0.00005 Loss 0.0456 (0.0326) Prec@1 99.219 (99.574) Prec@5 100.000 (100.000)
Train Epoch: [28][21/47],lr: 0.00005 Loss 0.0448 (0.0315) Prec@1 100.000 (99.740) Prec@5 100.000 (100.000)
Train Epoch: [28][31/47],lr: 0.00005 Loss 0.0192 (0.0346) Prec@1 100.000 (99.698) Prec@5 100.000 (100.000)
Train Epoch: [28][41/47],lr: 0.00005 Loss 0.0174 (0.0321) Prec@1 100.000 (99.771) Prec@5 100.000 (100.000)
Train Epoch: [28][47/47],lr: 0.00005 Loss 0.0295 (0.0347) Prec@1 100.000 (99.733) Prec@5 100.000 (99.967)
Val Epoch: [28][1/46] Loss 0.6863 (0.6863)
Cls@1:0.805 Cls@5:0.969
Loc@1:0.734 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [28][11/46] Loss 0.6661 (0.8185)
Cls@1:0.785 Cls@5:0.951
Loc@1:0.667 Loc@5:0.810 Loc_gt:0.853

Val Epoch: [28][21/46] Loss 0.5764 (0.7595)
Cls@1:0.803 Cls@5:0.955
Loc@1:0.699 Loc@5:0.832 Loc_gt:0.870

Val Epoch: [28][31/46] Loss 1.2743 (0.8586)
Cls@1:0.786 Cls@5:0.944
Loc@1:0.679 Loc@5:0.815 Loc_gt:0.860

Val Epoch: [28][41/46] Loss 1.0549 (0.8437)
Cls@1:0.791 Cls@5:0.945
Loc@1:0.680 Loc@5:0.813 Loc_gt:0.856

Val Epoch: [28][46/46] Loss 0.1534 (0.8173)
Cls@1:0.798 Cls@5:0.947
Loc@1:0.686 Loc@5:0.814 Loc_gt:0.856

wrong_details:3975 1171 0 525 119 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-57
Train Epoch: [29][1/47],lr: 0.00005 Loss 0.0273 (0.0273) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [29][11/47],lr: 0.00005 Loss 0.0409 (0.0502) Prec@1 99.219 (99.290) Prec@5 100.000 (100.000)
Train Epoch: [29][21/47],lr: 0.00005 Loss 0.0144 (0.0429) Prec@1 100.000 (99.516) Prec@5 100.000 (100.000)
Train Epoch: [29][31/47],lr: 0.00005 Loss 0.0186 (0.0427) Prec@1 100.000 (99.471) Prec@5 100.000 (100.000)
Train Epoch: [29][41/47],lr: 0.00005 Loss 0.0409 (0.0416) Prec@1 100.000 (99.486) Prec@5 100.000 (100.000)
Train Epoch: [29][47/47],lr: 0.00005 Loss 0.0430 (0.0408) Prec@1 100.000 (99.516) Prec@5 100.000 (100.000)
Val Epoch: [29][1/46] Loss 0.7050 (0.7050)
Cls@1:0.805 Cls@5:0.977
Loc@1:0.734 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [29][11/46] Loss 0.6299 (0.8286)
Cls@1:0.787 Cls@5:0.948
Loc@1:0.675 Loc@5:0.813 Loc_gt:0.857

Val Epoch: [29][21/46] Loss 0.5949 (0.7651)
Cls@1:0.805 Cls@5:0.952
Loc@1:0.703 Loc@5:0.833 Loc_gt:0.872

Val Epoch: [29][31/46] Loss 1.2140 (0.8777)
Cls@1:0.784 Cls@5:0.939
Loc@1:0.679 Loc@5:0.812 Loc_gt:0.861

Val Epoch: [29][41/46] Loss 0.9861 (0.8608)
Cls@1:0.790 Cls@5:0.941
Loc@1:0.678 Loc@5:0.808 Loc_gt:0.855

Val Epoch: [29][46/46] Loss 0.3091 (0.8292)
Cls@1:0.798 Cls@5:0.944
Loc@1:0.685 Loc@5:0.811 Loc_gt:0.855

wrong_details:3970 1169 0 541 108 6
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-58
Train Epoch: [30][1/47],lr: 0.00001 Loss 0.0328 (0.0328) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [30][11/47],lr: 0.00001 Loss 0.0518 (0.0341) Prec@1 97.656 (99.574) Prec@5 100.000 (100.000)
Train Epoch: [30][21/47],lr: 0.00001 Loss 0.0290 (0.0406) Prec@1 100.000 (99.554) Prec@5 100.000 (100.000)
Train Epoch: [30][31/47],lr: 0.00001 Loss 0.0209 (0.0375) Prec@1 100.000 (99.597) Prec@5 100.000 (100.000)
Train Epoch: [30][41/47],lr: 0.00001 Loss 0.0135 (0.0370) Prec@1 100.000 (99.619) Prec@5 100.000 (100.000)
Train Epoch: [30][47/47],lr: 0.00001 Loss 0.0469 (0.0374) Prec@1 100.000 (99.666) Prec@5 100.000 (100.000)
Val Epoch: [30][1/46] Loss 0.6972 (0.6972)
Cls@1:0.797 Cls@5:0.977
Loc@1:0.727 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [30][11/46] Loss 0.6260 (0.8126)
Cls@1:0.788 Cls@5:0.950
Loc@1:0.671 Loc@5:0.808 Loc_gt:0.852

Val Epoch: [30][21/46] Loss 0.6014 (0.7543)
Cls@1:0.807 Cls@5:0.953
Loc@1:0.702 Loc@5:0.830 Loc_gt:0.869

Val Epoch: [30][31/46] Loss 1.2090 (0.8671)
Cls@1:0.786 Cls@5:0.941
Loc@1:0.678 Loc@5:0.810 Loc_gt:0.859

Val Epoch: [30][41/46] Loss 0.9895 (0.8508)
Cls@1:0.793 Cls@5:0.942
Loc@1:0.679 Loc@5:0.807 Loc_gt:0.853

Val Epoch: [30][46/46] Loss 0.2601 (0.8199)
Cls@1:0.801 Cls@5:0.945
Loc@1:0.687 Loc@5:0.810 Loc_gt:0.854

wrong_details:3979 1151 0 550 110 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-19-59
Train Epoch: [31][1/47],lr: 0.00001 Loss 0.0371 (0.0371) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [31][11/47],lr: 0.00001 Loss 0.0251 (0.0299) Prec@1 99.219 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [31][21/47],lr: 0.00001 Loss 0.0227 (0.0258) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [31][31/47],lr: 0.00001 Loss 0.0113 (0.0260) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [31][41/47],lr: 0.00001 Loss 0.0448 (0.0277) Prec@1 98.438 (99.752) Prec@5 100.000 (100.000)
Train Epoch: [31][47/47],lr: 0.00001 Loss 0.0164 (0.0292) Prec@1 100.000 (99.733) Prec@5 100.000 (100.000)
Val Epoch: [31][1/46] Loss 0.6827 (0.6827)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.727 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [31][11/46] Loss 0.6120 (0.8149)
Cls@1:0.787 Cls@5:0.949
Loc@1:0.667 Loc@5:0.805 Loc_gt:0.848

Val Epoch: [31][21/46] Loss 0.5953 (0.7556)
Cls@1:0.805 Cls@5:0.953
Loc@1:0.697 Loc@5:0.827 Loc_gt:0.866

Val Epoch: [31][31/46] Loss 1.2146 (0.8640)
Cls@1:0.786 Cls@5:0.940
Loc@1:0.675 Loc@5:0.807 Loc_gt:0.855

Val Epoch: [31][41/46] Loss 0.9993 (0.8469)
Cls@1:0.793 Cls@5:0.942
Loc@1:0.676 Loc@5:0.804 Loc_gt:0.849

Val Epoch: [31][46/46] Loss 0.2396 (0.8163)
Cls@1:0.801 Cls@5:0.944
Loc@1:0.683 Loc@5:0.807 Loc_gt:0.851

wrong_details:3960 1151 0 568 111 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-00
Train Epoch: [32][1/47],lr: 0.00001 Loss 0.0252 (0.0252) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [32][11/47],lr: 0.00001 Loss 0.0173 (0.0286) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [32][21/47],lr: 0.00001 Loss 0.0459 (0.0351) Prec@1 99.219 (99.628) Prec@5 100.000 (100.000)
Train Epoch: [32][31/47],lr: 0.00001 Loss 0.0147 (0.0322) Prec@1 100.000 (99.748) Prec@5 100.000 (100.000)
Train Epoch: [32][41/47],lr: 0.00001 Loss 0.0259 (0.0321) Prec@1 100.000 (99.714) Prec@5 100.000 (100.000)
Train Epoch: [32][47/47],lr: 0.00001 Loss 0.0193 (0.0305) Prec@1 100.000 (99.750) Prec@5 100.000 (100.000)
Val Epoch: [32][1/46] Loss 0.6772 (0.6772)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.727 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [32][11/46] Loss 0.6106 (0.8079)
Cls@1:0.786 Cls@5:0.952
Loc@1:0.663 Loc@5:0.805 Loc_gt:0.844

Val Epoch: [32][21/46] Loss 0.5853 (0.7521)
Cls@1:0.805 Cls@5:0.954
Loc@1:0.695 Loc@5:0.826 Loc_gt:0.863

Val Epoch: [32][31/46] Loss 1.2256 (0.8611)
Cls@1:0.787 Cls@5:0.940
Loc@1:0.673 Loc@5:0.804 Loc_gt:0.853

Val Epoch: [32][41/46] Loss 0.9825 (0.8449)
Cls@1:0.794 Cls@5:0.941
Loc@1:0.674 Loc@5:0.801 Loc_gt:0.846

Val Epoch: [32][46/46] Loss 0.2181 (0.8138)
Cls@1:0.803 Cls@5:0.944
Loc@1:0.682 Loc@5:0.804 Loc_gt:0.847

wrong_details:3950 1144 0 591 105 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-01
Train Epoch: [33][1/47],lr: 0.00001 Loss 0.0153 (0.0153) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [33][11/47],lr: 0.00001 Loss 0.0220 (0.0312) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [33][21/47],lr: 0.00001 Loss 0.0563 (0.0327) Prec@1 100.000 (99.702) Prec@5 100.000 (100.000)
Train Epoch: [33][31/47],lr: 0.00001 Loss 0.0230 (0.0331) Prec@1 100.000 (99.723) Prec@5 100.000 (100.000)
Train Epoch: [33][41/47],lr: 0.00001 Loss 0.0432 (0.0335) Prec@1 99.219 (99.714) Prec@5 100.000 (100.000)
Train Epoch: [33][47/47],lr: 0.00001 Loss 0.0300 (0.0323) Prec@1 100.000 (99.750) Prec@5 100.000 (100.000)
Val Epoch: [33][1/46] Loss 0.6710 (0.6710)
Cls@1:0.805 Cls@5:0.969
Loc@1:0.734 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [33][11/46] Loss 0.6139 (0.8021)
Cls@1:0.787 Cls@5:0.953
Loc@1:0.665 Loc@5:0.805 Loc_gt:0.844

Val Epoch: [33][21/46] Loss 0.5880 (0.7487)
Cls@1:0.806 Cls@5:0.955
Loc@1:0.696 Loc@5:0.826 Loc_gt:0.863

Val Epoch: [33][31/46] Loss 1.2156 (0.8560)
Cls@1:0.787 Cls@5:0.942
Loc@1:0.675 Loc@5:0.807 Loc_gt:0.854

Val Epoch: [33][41/46] Loss 0.9797 (0.8402)
Cls@1:0.795 Cls@5:0.943
Loc@1:0.675 Loc@5:0.802 Loc_gt:0.847

Val Epoch: [33][46/46] Loss 0.2156 (0.8092)
Cls@1:0.803 Cls@5:0.946
Loc@1:0.683 Loc@5:0.805 Loc_gt:0.848

wrong_details:3958 1140 0 582 110 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-02
Train Epoch: [34][1/47],lr: 0.00001 Loss 0.0341 (0.0341) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [34][11/47],lr: 0.00001 Loss 0.0240 (0.0397) Prec@1 99.219 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [34][21/47],lr: 0.00001 Loss 0.0256 (0.0372) Prec@1 100.000 (99.702) Prec@5 100.000 (100.000)
Train Epoch: [34][31/47],lr: 0.00001 Loss 0.0163 (0.0385) Prec@1 100.000 (99.622) Prec@5 100.000 (100.000)
Train Epoch: [34][41/47],lr: 0.00001 Loss 0.0224 (0.0346) Prec@1 100.000 (99.676) Prec@5 100.000 (100.000)
Train Epoch: [34][47/47],lr: 0.00001 Loss 0.0416 (0.0351) Prec@1 100.000 (99.683) Prec@5 100.000 (100.000)
Val Epoch: [34][1/46] Loss 0.6695 (0.6695)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.727 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [34][11/46] Loss 0.6127 (0.8078)
Cls@1:0.788 Cls@5:0.951
Loc@1:0.664 Loc@5:0.801 Loc_gt:0.842

Val Epoch: [34][21/46] Loss 0.5942 (0.7514)
Cls@1:0.807 Cls@5:0.954
Loc@1:0.696 Loc@5:0.824 Loc_gt:0.862

Val Epoch: [34][31/46] Loss 1.2354 (0.8566)
Cls@1:0.788 Cls@5:0.941
Loc@1:0.674 Loc@5:0.805 Loc_gt:0.852

Val Epoch: [34][41/46] Loss 0.9909 (0.8411)
Cls@1:0.795 Cls@5:0.942
Loc@1:0.673 Loc@5:0.800 Loc_gt:0.844

Val Epoch: [34][46/46] Loss 0.1909 (0.8102)
Cls@1:0.804 Cls@5:0.944
Loc@1:0.682 Loc@5:0.802 Loc_gt:0.846

wrong_details:3950 1135 0 598 107 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-03
Train Epoch: [35][1/47],lr: 0.00001 Loss 0.0438 (0.0438) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [35][11/47],lr: 0.00001 Loss 0.0240 (0.0328) Prec@1 100.000 (99.716) Prec@5 100.000 (99.929)
Train Epoch: [35][21/47],lr: 0.00001 Loss 0.0205 (0.0395) Prec@1 99.219 (99.479) Prec@5 100.000 (99.963)
Train Epoch: [35][31/47],lr: 0.00001 Loss 0.0126 (0.0334) Prec@1 100.000 (99.622) Prec@5 100.000 (99.975)
Train Epoch: [35][41/47],lr: 0.00001 Loss 0.0310 (0.0293) Prec@1 100.000 (99.676) Prec@5 100.000 (99.981)
Train Epoch: [35][47/47],lr: 0.00001 Loss 0.0187 (0.0299) Prec@1 99.057 (99.683) Prec@5 100.000 (99.983)
Val Epoch: [35][1/46] Loss 0.6659 (0.6659)
Cls@1:0.805 Cls@5:0.969
Loc@1:0.734 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [35][11/46] Loss 0.6031 (0.8026)
Cls@1:0.790 Cls@5:0.952
Loc@1:0.666 Loc@5:0.804 Loc_gt:0.844

Val Epoch: [35][21/46] Loss 0.5970 (0.7481)
Cls@1:0.809 Cls@5:0.954
Loc@1:0.701 Loc@5:0.826 Loc_gt:0.863

Val Epoch: [35][31/46] Loss 1.2311 (0.8555)
Cls@1:0.789 Cls@5:0.941
Loc@1:0.676 Loc@5:0.806 Loc_gt:0.853

Val Epoch: [35][41/46] Loss 1.0093 (0.8405)
Cls@1:0.797 Cls@5:0.943
Loc@1:0.675 Loc@5:0.801 Loc_gt:0.845

Val Epoch: [35][46/46] Loss 0.1992 (0.8102)
Cls@1:0.805 Cls@5:0.945
Loc@1:0.683 Loc@5:0.803 Loc_gt:0.846

wrong_details:3956 1130 0 604 100 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-04
Train Epoch: [36][1/47],lr: 0.00001 Loss 0.0188 (0.0188) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [36][11/47],lr: 0.00001 Loss 0.0113 (0.0268) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [36][21/47],lr: 0.00001 Loss 0.0535 (0.0295) Prec@1 100.000 (99.851) Prec@5 100.000 (99.963)
Train Epoch: [36][31/47],lr: 0.00001 Loss 0.0453 (0.0299) Prec@1 100.000 (99.798) Prec@5 100.000 (99.975)
Train Epoch: [36][41/47],lr: 0.00001 Loss 0.0347 (0.0292) Prec@1 99.219 (99.733) Prec@5 100.000 (99.981)
Train Epoch: [36][47/47],lr: 0.00001 Loss 0.0239 (0.0283) Prec@1 100.000 (99.766) Prec@5 100.000 (99.983)
Val Epoch: [36][1/46] Loss 0.6583 (0.6583)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.727 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [36][11/46] Loss 0.6159 (0.8011)
Cls@1:0.786 Cls@5:0.955
Loc@1:0.669 Loc@5:0.810 Loc_gt:0.848

Val Epoch: [36][21/46] Loss 0.5884 (0.7472)
Cls@1:0.806 Cls@5:0.955
Loc@1:0.703 Loc@5:0.830 Loc_gt:0.868

Val Epoch: [36][31/46] Loss 1.2281 (0.8552)
Cls@1:0.786 Cls@5:0.943
Loc@1:0.679 Loc@5:0.811 Loc_gt:0.857

Val Epoch: [36][41/46] Loss 1.0120 (0.8396)
Cls@1:0.794 Cls@5:0.944
Loc@1:0.678 Loc@5:0.806 Loc_gt:0.849

Val Epoch: [36][46/46] Loss 0.1971 (0.8091)
Cls@1:0.803 Cls@5:0.946
Loc@1:0.685 Loc@5:0.808 Loc_gt:0.850

wrong_details:3970 1144 0 575 101 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-05
Train Epoch: [37][1/47],lr: 0.00001 Loss 0.0148 (0.0148) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [37][11/47],lr: 0.00001 Loss 0.0932 (0.0314) Prec@1 96.875 (99.574) Prec@5 100.000 (100.000)
Train Epoch: [37][21/47],lr: 0.00001 Loss 0.0406 (0.0321) Prec@1 100.000 (99.554) Prec@5 100.000 (99.963)
Train Epoch: [37][31/47],lr: 0.00001 Loss 0.0179 (0.0381) Prec@1 100.000 (99.471) Prec@5 100.000 (99.975)
Train Epoch: [37][41/47],lr: 0.00001 Loss 0.0265 (0.0347) Prec@1 100.000 (99.581) Prec@5 100.000 (99.981)
Train Epoch: [37][47/47],lr: 0.00001 Loss 0.0218 (0.0331) Prec@1 100.000 (99.633) Prec@5 100.000 (99.983)
Val Epoch: [37][1/46] Loss 0.6484 (0.6484)
Cls@1:0.805 Cls@5:0.969
Loc@1:0.734 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [37][11/46] Loss 0.6447 (0.8069)
Cls@1:0.786 Cls@5:0.952
Loc@1:0.663 Loc@5:0.804 Loc_gt:0.844

Val Epoch: [37][21/46] Loss 0.5870 (0.7514)
Cls@1:0.807 Cls@5:0.953
Loc@1:0.700 Loc@5:0.827 Loc_gt:0.866

Val Epoch: [37][31/46] Loss 1.2372 (0.8565)
Cls@1:0.789 Cls@5:0.943
Loc@1:0.680 Loc@5:0.810 Loc_gt:0.856

Val Epoch: [37][41/46] Loss 1.0102 (0.8414)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.679 Loc@5:0.805 Loc_gt:0.849

Val Epoch: [37][46/46] Loss 0.1854 (0.8112)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.686 Loc@5:0.807 Loc_gt:0.849

wrong_details:3975 1134 0 580 100 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-06
Train Epoch: [38][1/47],lr: 0.00001 Loss 0.0183 (0.0183) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [38][11/47],lr: 0.00001 Loss 0.0284 (0.0356) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [38][21/47],lr: 0.00001 Loss 0.0174 (0.0312) Prec@1 100.000 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [38][31/47],lr: 0.00001 Loss 0.0164 (0.0286) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [38][41/47],lr: 0.00001 Loss 0.0192 (0.0291) Prec@1 100.000 (99.829) Prec@5 100.000 (100.000)
Train Epoch: [38][47/47],lr: 0.00001 Loss 0.0545 (0.0281) Prec@1 99.057 (99.833) Prec@5 100.000 (100.000)
Val Epoch: [38][1/46] Loss 0.6670 (0.6670)
Cls@1:0.805 Cls@5:0.969
Loc@1:0.734 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [38][11/46] Loss 0.6305 (0.8095)
Cls@1:0.786 Cls@5:0.950
Loc@1:0.668 Loc@5:0.808 Loc_gt:0.849

Val Epoch: [38][21/46] Loss 0.5886 (0.7523)
Cls@1:0.808 Cls@5:0.953
Loc@1:0.702 Loc@5:0.830 Loc_gt:0.869

Val Epoch: [38][31/46] Loss 1.2390 (0.8549)
Cls@1:0.789 Cls@5:0.942
Loc@1:0.681 Loc@5:0.812 Loc_gt:0.859

Val Epoch: [38][41/46] Loss 1.0021 (0.8394)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.682 Loc@5:0.808 Loc_gt:0.852

Val Epoch: [38][46/46] Loss 0.1830 (0.8095)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.689 Loc@5:0.811 Loc_gt:0.853

wrong_details:3992 1131 0 559 108 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-07
Train Epoch: [39][1/47],lr: 0.00001 Loss 0.0153 (0.0153) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [39][11/47],lr: 0.00001 Loss 0.0072 (0.0327) Prec@1 100.000 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [39][21/47],lr: 0.00001 Loss 0.0737 (0.0353) Prec@1 100.000 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [39][31/47],lr: 0.00001 Loss 0.1424 (0.0333) Prec@1 97.656 (99.773) Prec@5 99.219 (99.975)
Train Epoch: [39][41/47],lr: 0.00001 Loss 0.0243 (0.0339) Prec@1 100.000 (99.771) Prec@5 100.000 (99.981)
Train Epoch: [39][47/47],lr: 0.00001 Loss 0.0500 (0.0334) Prec@1 100.000 (99.766) Prec@5 100.000 (99.983)
Val Epoch: [39][1/46] Loss 0.6510 (0.6510)
Cls@1:0.812 Cls@5:0.969
Loc@1:0.734 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [39][11/46] Loss 0.6344 (0.8109)
Cls@1:0.783 Cls@5:0.949
Loc@1:0.664 Loc@5:0.803 Loc_gt:0.847

Val Epoch: [39][21/46] Loss 0.6016 (0.7543)
Cls@1:0.806 Cls@5:0.952
Loc@1:0.699 Loc@5:0.826 Loc_gt:0.867

Val Epoch: [39][31/46] Loss 1.2073 (0.8538)
Cls@1:0.789 Cls@5:0.942
Loc@1:0.678 Loc@5:0.809 Loc_gt:0.855

Val Epoch: [39][41/46] Loss 0.9970 (0.8386)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.677 Loc@5:0.804 Loc_gt:0.847

Val Epoch: [39][46/46] Loss 0.1618 (0.8088)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.686 Loc@5:0.807 Loc_gt:0.849

wrong_details:3975 1129 0 581 104 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-08
Train Epoch: [40][1/47],lr: 0.00001 Loss 0.0130 (0.0130) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [40][11/47],lr: 0.00001 Loss 0.0328 (0.0257) Prec@1 99.219 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [40][21/47],lr: 0.00001 Loss 0.0567 (0.0325) Prec@1 99.219 (99.702) Prec@5 100.000 (99.963)
Train Epoch: [40][31/47],lr: 0.00001 Loss 0.0250 (0.0278) Prec@1 100.000 (99.773) Prec@5 100.000 (99.975)
Train Epoch: [40][41/47],lr: 0.00001 Loss 0.0124 (0.0255) Prec@1 100.000 (99.809) Prec@5 100.000 (99.981)
Train Epoch: [40][47/47],lr: 0.00001 Loss 0.0152 (0.0241) Prec@1 100.000 (99.833) Prec@5 100.000 (99.983)
Val Epoch: [40][1/46] Loss 0.6553 (0.6553)
Cls@1:0.812 Cls@5:0.969
Loc@1:0.734 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [40][11/46] Loss 0.6350 (0.8077)
Cls@1:0.788 Cls@5:0.952
Loc@1:0.668 Loc@5:0.807 Loc_gt:0.847

Val Epoch: [40][21/46] Loss 0.5988 (0.7533)
Cls@1:0.808 Cls@5:0.954
Loc@1:0.702 Loc@5:0.828 Loc_gt:0.866

Val Epoch: [40][31/46] Loss 1.2288 (0.8542)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.680 Loc@5:0.808 Loc_gt:0.855

Val Epoch: [40][41/46] Loss 0.9946 (0.8393)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.679 Loc@5:0.805 Loc_gt:0.849

Val Epoch: [40][46/46] Loss 0.1674 (0.8088)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.688 Loc@5:0.808 Loc_gt:0.850

wrong_details:3984 1130 0 577 100 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-09
Train Epoch: [41][1/47],lr: 0.00001 Loss 0.0172 (0.0172) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [41][11/47],lr: 0.00001 Loss 0.0136 (0.0173) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [41][21/47],lr: 0.00001 Loss 0.0241 (0.0251) Prec@1 100.000 (99.926) Prec@5 100.000 (100.000)
Train Epoch: [41][31/47],lr: 0.00001 Loss 0.0168 (0.0269) Prec@1 100.000 (99.798) Prec@5 100.000 (100.000)
Train Epoch: [41][41/47],lr: 0.00001 Loss 0.0536 (0.0263) Prec@1 98.438 (99.752) Prec@5 100.000 (100.000)
Train Epoch: [41][47/47],lr: 0.00001 Loss 0.0749 (0.0266) Prec@1 98.113 (99.716) Prec@5 100.000 (100.000)
Val Epoch: [41][1/46] Loss 0.6540 (0.6540)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [41][11/46] Loss 0.6393 (0.8125)
Cls@1:0.789 Cls@5:0.952
Loc@1:0.667 Loc@5:0.805 Loc_gt:0.845

Val Epoch: [41][21/46] Loss 0.6046 (0.7562)
Cls@1:0.808 Cls@5:0.954
Loc@1:0.701 Loc@5:0.826 Loc_gt:0.865

Val Epoch: [41][31/46] Loss 1.2075 (0.8589)
Cls@1:0.791 Cls@5:0.941
Loc@1:0.679 Loc@5:0.806 Loc_gt:0.853

Val Epoch: [41][41/46] Loss 0.9830 (0.8428)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.679 Loc@5:0.804 Loc_gt:0.848

Val Epoch: [41][46/46] Loss 0.1886 (0.8124)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.687 Loc@5:0.807 Loc_gt:0.849

wrong_details:3980 1128 0 580 102 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-10
Train Epoch: [42][1/47],lr: 0.00001 Loss 0.0125 (0.0125) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [42][11/47],lr: 0.00001 Loss 0.0093 (0.0261) Prec@1 100.000 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [42][21/47],lr: 0.00001 Loss 0.0089 (0.0252) Prec@1 100.000 (99.740) Prec@5 100.000 (100.000)
Train Epoch: [42][31/47],lr: 0.00001 Loss 0.0105 (0.0271) Prec@1 100.000 (99.748) Prec@5 100.000 (100.000)
Train Epoch: [42][41/47],lr: 0.00001 Loss 0.0230 (0.0271) Prec@1 100.000 (99.752) Prec@5 100.000 (100.000)
Train Epoch: [42][47/47],lr: 0.00001 Loss 0.0159 (0.0261) Prec@1 100.000 (99.750) Prec@5 100.000 (100.000)
Val Epoch: [42][1/46] Loss 0.6590 (0.6590)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.734 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [42][11/46] Loss 0.6313 (0.8145)
Cls@1:0.790 Cls@5:0.950
Loc@1:0.662 Loc@5:0.797 Loc_gt:0.839

Val Epoch: [42][21/46] Loss 0.5825 (0.7573)
Cls@1:0.809 Cls@5:0.952
Loc@1:0.698 Loc@5:0.822 Loc_gt:0.862

Val Epoch: [42][31/46] Loss 1.2145 (0.8609)
Cls@1:0.792 Cls@5:0.941
Loc@1:0.678 Loc@5:0.804 Loc_gt:0.851

Val Epoch: [42][41/46] Loss 0.9773 (0.8437)
Cls@1:0.799 Cls@5:0.944
Loc@1:0.677 Loc@5:0.800 Loc_gt:0.844

Val Epoch: [42][46/46] Loss 0.1821 (0.8133)
Cls@1:0.807 Cls@5:0.945
Loc@1:0.685 Loc@5:0.803 Loc_gt:0.846

wrong_details:3971 1118 0 604 97 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-11
Train Epoch: [43][1/47],lr: 0.00001 Loss 0.0247 (0.0247) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [43][11/47],lr: 0.00001 Loss 0.0216 (0.0194) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [43][21/47],lr: 0.00001 Loss 0.0177 (0.0247) Prec@1 100.000 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [43][31/47],lr: 0.00001 Loss 0.0101 (0.0249) Prec@1 100.000 (99.849) Prec@5 100.000 (100.000)
Train Epoch: [43][41/47],lr: 0.00001 Loss 0.0702 (0.0249) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [43][47/47],lr: 0.00001 Loss 0.0252 (0.0244) Prec@1 100.000 (99.850) Prec@5 100.000 (100.000)
Val Epoch: [43][1/46] Loss 0.6481 (0.6481)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [43][11/46] Loss 0.6389 (0.8137)
Cls@1:0.790 Cls@5:0.952
Loc@1:0.665 Loc@5:0.802 Loc_gt:0.842

Val Epoch: [43][21/46] Loss 0.5678 (0.7534)
Cls@1:0.811 Cls@5:0.953
Loc@1:0.704 Loc@5:0.827 Loc_gt:0.866

Val Epoch: [43][31/46] Loss 1.2059 (0.8560)
Cls@1:0.793 Cls@5:0.942
Loc@1:0.683 Loc@5:0.809 Loc_gt:0.855

Val Epoch: [43][41/46] Loss 0.9958 (0.8417)
Cls@1:0.798 Cls@5:0.944
Loc@1:0.681 Loc@5:0.806 Loc_gt:0.849

Val Epoch: [43][46/46] Loss 0.1661 (0.8114)
Cls@1:0.807 Cls@5:0.946
Loc@1:0.689 Loc@5:0.809 Loc_gt:0.850

wrong_details:3994 1119 0 581 96 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-12
Train Epoch: [44][1/47],lr: 0.00001 Loss 0.0245 (0.0245) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [44][11/47],lr: 0.00001 Loss 0.0164 (0.0325) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [44][21/47],lr: 0.00001 Loss 0.0137 (0.0280) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [44][31/47],lr: 0.00001 Loss 0.0149 (0.0259) Prec@1 100.000 (99.899) Prec@5 100.000 (100.000)
Train Epoch: [44][41/47],lr: 0.00001 Loss 0.0194 (0.0266) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [44][47/47],lr: 0.00001 Loss 0.0288 (0.0266) Prec@1 99.057 (99.833) Prec@5 100.000 (100.000)
Val Epoch: [44][1/46] Loss 0.6674 (0.6674)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [44][11/46] Loss 0.6297 (0.8148)
Cls@1:0.788 Cls@5:0.950
Loc@1:0.663 Loc@5:0.800 Loc_gt:0.843

Val Epoch: [44][21/46] Loss 0.5779 (0.7555)
Cls@1:0.808 Cls@5:0.952
Loc@1:0.702 Loc@5:0.825 Loc_gt:0.866

Val Epoch: [44][31/46] Loss 1.2024 (0.8574)
Cls@1:0.790 Cls@5:0.941
Loc@1:0.680 Loc@5:0.808 Loc_gt:0.856

Val Epoch: [44][41/46] Loss 1.0113 (0.8408)
Cls@1:0.797 Cls@5:0.943
Loc@1:0.678 Loc@5:0.805 Loc_gt:0.849

Val Epoch: [44][46/46] Loss 0.1794 (0.8104)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.686 Loc@5:0.808 Loc_gt:0.850

wrong_details:3977 1130 0 586 96 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-13
Train Epoch: [45][1/47],lr: 0.00001 Loss 0.0129 (0.0129) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [45][11/47],lr: 0.00001 Loss 0.0111 (0.0223) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [45][21/47],lr: 0.00001 Loss 0.0241 (0.0219) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [45][31/47],lr: 0.00001 Loss 0.0312 (0.0233) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [45][41/47],lr: 0.00001 Loss 0.0463 (0.0222) Prec@1 99.219 (99.886) Prec@5 100.000 (100.000)
Train Epoch: [45][47/47],lr: 0.00001 Loss 0.0092 (0.0220) Prec@1 100.000 (99.900) Prec@5 100.000 (100.000)
Val Epoch: [45][1/46] Loss 0.6657 (0.6657)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.742 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [45][11/46] Loss 0.6328 (0.8163)
Cls@1:0.790 Cls@5:0.952
Loc@1:0.667 Loc@5:0.803 Loc_gt:0.844

Val Epoch: [45][21/46] Loss 0.6010 (0.7589)
Cls@1:0.808 Cls@5:0.953
Loc@1:0.702 Loc@5:0.827 Loc_gt:0.867

Val Epoch: [45][31/46] Loss 1.2104 (0.8601)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.680 Loc@5:0.810 Loc_gt:0.857

Val Epoch: [45][41/46] Loss 0.9860 (0.8424)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.679 Loc@5:0.806 Loc_gt:0.850

Val Epoch: [45][46/46] Loss 0.1754 (0.8121)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.687 Loc@5:0.809 Loc_gt:0.852

wrong_details:3982 1129 0 577 102 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-14
Train Epoch: [46][1/47],lr: 0.00001 Loss 0.0297 (0.0297) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [46][11/47],lr: 0.00001 Loss 0.0203 (0.0199) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [46][21/47],lr: 0.00001 Loss 0.0142 (0.0231) Prec@1 100.000 (99.926) Prec@5 100.000 (100.000)
Train Epoch: [46][31/47],lr: 0.00001 Loss 0.0177 (0.0219) Prec@1 100.000 (99.950) Prec@5 100.000 (100.000)
Train Epoch: [46][41/47],lr: 0.00001 Loss 0.0126 (0.0233) Prec@1 100.000 (99.886) Prec@5 100.000 (100.000)
Train Epoch: [46][47/47],lr: 0.00001 Loss 0.0282 (0.0233) Prec@1 99.057 (99.833) Prec@5 100.000 (100.000)
Val Epoch: [46][1/46] Loss 0.6660 (0.6660)
Cls@1:0.812 Cls@5:0.969
Loc@1:0.727 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [46][11/46] Loss 0.6320 (0.8138)
Cls@1:0.792 Cls@5:0.955
Loc@1:0.668 Loc@5:0.805 Loc_gt:0.843

Val Epoch: [46][21/46] Loss 0.5948 (0.7551)
Cls@1:0.810 Cls@5:0.955
Loc@1:0.702 Loc@5:0.827 Loc_gt:0.865

Val Epoch: [46][31/46] Loss 1.2014 (0.8607)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.680 Loc@5:0.809 Loc_gt:0.855

Val Epoch: [46][41/46] Loss 0.9922 (0.8440)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.679 Loc@5:0.805 Loc_gt:0.849

Val Epoch: [46][46/46] Loss 0.1673 (0.8128)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.687 Loc@5:0.808 Loc_gt:0.850

wrong_details:3978 1128 0 590 95 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-15
Train Epoch: [47][1/47],lr: 0.00001 Loss 0.0446 (0.0446) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [47][11/47],lr: 0.00001 Loss 0.0117 (0.0269) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [47][21/47],lr: 0.00001 Loss 0.0976 (0.0283) Prec@1 99.219 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [47][31/47],lr: 0.00001 Loss 0.0055 (0.0285) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [47][41/47],lr: 0.00001 Loss 0.0282 (0.0315) Prec@1 100.000 (99.771) Prec@5 100.000 (100.000)
Train Epoch: [47][47/47],lr: 0.00001 Loss 0.0210 (0.0298) Prec@1 100.000 (99.783) Prec@5 100.000 (100.000)
Val Epoch: [47][1/46] Loss 0.6715 (0.6715)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.750 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [47][11/46] Loss 0.6043 (0.8174)
Cls@1:0.788 Cls@5:0.952
Loc@1:0.664 Loc@5:0.800 Loc_gt:0.842

Val Epoch: [47][21/46] Loss 0.5917 (0.7624)
Cls@1:0.807 Cls@5:0.953
Loc@1:0.699 Loc@5:0.824 Loc_gt:0.863

Val Epoch: [47][31/46] Loss 1.2202 (0.8661)
Cls@1:0.789 Cls@5:0.942
Loc@1:0.678 Loc@5:0.808 Loc_gt:0.854

Val Epoch: [47][41/46] Loss 0.9699 (0.8462)
Cls@1:0.795 Cls@5:0.945
Loc@1:0.676 Loc@5:0.804 Loc_gt:0.847

Val Epoch: [47][46/46] Loss 0.1800 (0.8153)
Cls@1:0.804 Cls@5:0.947
Loc@1:0.685 Loc@5:0.807 Loc_gt:0.849

wrong_details:3968 1136 0 595 92 3
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-16
Train Epoch: [48][1/47],lr: 0.00001 Loss 0.0302 (0.0302) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [48][11/47],lr: 0.00001 Loss 0.0276 (0.0189) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [48][21/47],lr: 0.00001 Loss 0.0585 (0.0228) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [48][31/47],lr: 0.00001 Loss 0.0253 (0.0224) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [48][41/47],lr: 0.00001 Loss 0.0226 (0.0213) Prec@1 99.219 (99.886) Prec@5 100.000 (100.000)
Train Epoch: [48][47/47],lr: 0.00001 Loss 0.0063 (0.0208) Prec@1 100.000 (99.883) Prec@5 100.000 (100.000)
Val Epoch: [48][1/46] Loss 0.6434 (0.6434)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.734 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [48][11/46] Loss 0.6128 (0.8050)
Cls@1:0.794 Cls@5:0.954
Loc@1:0.670 Loc@5:0.803 Loc_gt:0.842

Val Epoch: [48][21/46] Loss 0.5854 (0.7562)
Cls@1:0.811 Cls@5:0.954
Loc@1:0.703 Loc@5:0.824 Loc_gt:0.862

Val Epoch: [48][31/46] Loss 1.2169 (0.8611)
Cls@1:0.791 Cls@5:0.942
Loc@1:0.679 Loc@5:0.805 Loc_gt:0.852

Val Epoch: [48][41/46] Loss 0.9664 (0.8429)
Cls@1:0.798 Cls@5:0.944
Loc@1:0.679 Loc@5:0.803 Loc_gt:0.846

Val Epoch: [48][46/46] Loss 0.1676 (0.8119)
Cls@1:0.807 Cls@5:0.946
Loc@1:0.687 Loc@5:0.806 Loc_gt:0.848

wrong_details:3981 1121 0 594 94 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-17
Train Epoch: [49][1/47],lr: 0.00001 Loss 0.0157 (0.0157) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [49][11/47],lr: 0.00001 Loss 0.0326 (0.0181) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [49][21/47],lr: 0.00001 Loss 0.0246 (0.0173) Prec@1 100.000 (99.963) Prec@5 100.000 (100.000)
Train Epoch: [49][31/47],lr: 0.00001 Loss 0.0327 (0.0200) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [49][41/47],lr: 0.00001 Loss 0.0122 (0.0219) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [49][47/47],lr: 0.00001 Loss 0.0102 (0.0212) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [49][1/46] Loss 0.6472 (0.6472)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.734 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [49][11/46] Loss 0.6436 (0.8064)
Cls@1:0.794 Cls@5:0.952
Loc@1:0.666 Loc@5:0.799 Loc_gt:0.839

Val Epoch: [49][21/46] Loss 0.5999 (0.7569)
Cls@1:0.809 Cls@5:0.954
Loc@1:0.698 Loc@5:0.822 Loc_gt:0.860

Val Epoch: [49][31/46] Loss 1.2019 (0.8619)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.677 Loc@5:0.804 Loc_gt:0.851

Val Epoch: [49][41/46] Loss 0.9451 (0.8451)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.676 Loc@5:0.801 Loc_gt:0.845

Val Epoch: [49][46/46] Loss 0.1881 (0.8144)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.684 Loc@5:0.804 Loc_gt:0.846

wrong_details:3962 1131 0 601 96 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-18
Train Epoch: [50][1/47],lr: 0.00001 Loss 0.0424 (0.0424) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [50][11/47],lr: 0.00001 Loss 0.0067 (0.0247) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [50][21/47],lr: 0.00001 Loss 0.0276 (0.0245) Prec@1 100.000 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [50][31/47],lr: 0.00001 Loss 0.0076 (0.0239) Prec@1 100.000 (99.824) Prec@5 100.000 (99.975)
Train Epoch: [50][41/47],lr: 0.00001 Loss 0.0199 (0.0226) Prec@1 100.000 (99.867) Prec@5 100.000 (99.981)
Train Epoch: [50][47/47],lr: 0.00001 Loss 0.0072 (0.0228) Prec@1 100.000 (99.883) Prec@5 100.000 (99.983)
Val Epoch: [50][1/46] Loss 0.6532 (0.6532)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.742 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [50][11/46] Loss 0.6259 (0.8077)
Cls@1:0.794 Cls@5:0.952
Loc@1:0.665 Loc@5:0.799 Loc_gt:0.839

Val Epoch: [50][21/46] Loss 0.5977 (0.7589)
Cls@1:0.810 Cls@5:0.953
Loc@1:0.697 Loc@5:0.821 Loc_gt:0.860

Val Epoch: [50][31/46] Loss 1.2065 (0.8662)
Cls@1:0.788 Cls@5:0.941
Loc@1:0.674 Loc@5:0.804 Loc_gt:0.851

Val Epoch: [50][41/46] Loss 0.9551 (0.8490)
Cls@1:0.795 Cls@5:0.943
Loc@1:0.674 Loc@5:0.800 Loc_gt:0.845

Val Epoch: [50][46/46] Loss 0.1905 (0.8183)
Cls@1:0.803 Cls@5:0.945
Loc@1:0.681 Loc@5:0.802 Loc_gt:0.846

wrong_details:3946 1139 0 606 99 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-19
Train Epoch: [51][1/47],lr: 0.00001 Loss 0.0895 (0.0895) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [51][11/47],lr: 0.00001 Loss 0.0259 (0.0255) Prec@1 100.000 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [51][21/47],lr: 0.00001 Loss 0.0243 (0.0214) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [51][31/47],lr: 0.00001 Loss 0.0094 (0.0203) Prec@1 100.000 (99.798) Prec@5 100.000 (100.000)
Train Epoch: [51][41/47],lr: 0.00001 Loss 0.0199 (0.0222) Prec@1 99.219 (99.771) Prec@5 100.000 (100.000)
Train Epoch: [51][47/47],lr: 0.00001 Loss 0.0196 (0.0241) Prec@1 100.000 (99.783) Prec@5 100.000 (100.000)
Val Epoch: [51][1/46] Loss 0.6477 (0.6477)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [51][11/46] Loss 0.6208 (0.8086)
Cls@1:0.793 Cls@5:0.953
Loc@1:0.669 Loc@5:0.803 Loc_gt:0.843

Val Epoch: [51][21/46] Loss 0.5872 (0.7574)
Cls@1:0.810 Cls@5:0.954
Loc@1:0.702 Loc@5:0.825 Loc_gt:0.864

Val Epoch: [51][31/46] Loss 1.2128 (0.8623)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.680 Loc@5:0.808 Loc_gt:0.854

Val Epoch: [51][41/46] Loss 0.9784 (0.8461)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.679 Loc@5:0.805 Loc_gt:0.849

Val Epoch: [51][46/46] Loss 0.1910 (0.8157)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.686 Loc@5:0.808 Loc_gt:0.849

wrong_details:3976 1136 0 577 101 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-20
Train Epoch: [52][1/47],lr: 0.00001 Loss 0.0090 (0.0090) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [52][11/47],lr: 0.00001 Loss 0.0586 (0.0192) Prec@1 99.219 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [52][21/47],lr: 0.00001 Loss 0.0050 (0.0178) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [52][31/47],lr: 0.00001 Loss 0.0282 (0.0249) Prec@1 100.000 (99.849) Prec@5 100.000 (100.000)
Train Epoch: [52][41/47],lr: 0.00001 Loss 0.0136 (0.0233) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Train Epoch: [52][47/47],lr: 0.00001 Loss 0.0260 (0.0235) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [52][1/46] Loss 0.6375 (0.6375)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.758 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [52][11/46] Loss 0.6207 (0.8131)
Cls@1:0.793 Cls@5:0.950
Loc@1:0.668 Loc@5:0.800 Loc_gt:0.844

Val Epoch: [52][21/46] Loss 0.5707 (0.7605)
Cls@1:0.809 Cls@5:0.952
Loc@1:0.702 Loc@5:0.824 Loc_gt:0.866

Val Epoch: [52][31/46] Loss 1.2223 (0.8649)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.682 Loc@5:0.810 Loc_gt:0.857

Val Epoch: [52][41/46] Loss 0.9900 (0.8478)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.680 Loc@5:0.807 Loc_gt:0.851

Val Epoch: [52][46/46] Loss 0.1898 (0.8177)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.688 Loc@5:0.810 Loc_gt:0.852

wrong_details:3984 1136 0 568 102 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-21
Train Epoch: [53][1/47],lr: 0.00001 Loss 0.0128 (0.0128) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [53][11/47],lr: 0.00001 Loss 0.0132 (0.0177) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [53][21/47],lr: 0.00001 Loss 0.0195 (0.0185) Prec@1 100.000 (99.963) Prec@5 100.000 (100.000)
Train Epoch: [53][31/47],lr: 0.00001 Loss 0.0274 (0.0218) Prec@1 99.219 (99.899) Prec@5 100.000 (100.000)
Train Epoch: [53][41/47],lr: 0.00001 Loss 0.0073 (0.0204) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [53][47/47],lr: 0.00001 Loss 0.0190 (0.0210) Prec@1 100.000 (99.917) Prec@5 100.000 (100.000)
Val Epoch: [53][1/46] Loss 0.6425 (0.6425)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.750 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [53][11/46] Loss 0.6242 (0.8113)
Cls@1:0.793 Cls@5:0.955
Loc@1:0.668 Loc@5:0.805 Loc_gt:0.844

Val Epoch: [53][21/46] Loss 0.5710 (0.7580)
Cls@1:0.809 Cls@5:0.954
Loc@1:0.702 Loc@5:0.826 Loc_gt:0.865

Val Epoch: [53][31/46] Loss 1.2251 (0.8625)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.680 Loc@5:0.809 Loc_gt:0.855

Val Epoch: [53][41/46] Loss 1.0001 (0.8473)
Cls@1:0.795 Cls@5:0.944
Loc@1:0.678 Loc@5:0.805 Loc_gt:0.849

Val Epoch: [53][46/46] Loss 0.1967 (0.8167)
Cls@1:0.803 Cls@5:0.946
Loc@1:0.686 Loc@5:0.807 Loc_gt:0.849

wrong_details:3972 1140 0 575 102 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-22
Train Epoch: [54][1/47],lr: 0.00001 Loss 0.0419 (0.0419) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [54][11/47],lr: 0.00001 Loss 0.0090 (0.0248) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [54][21/47],lr: 0.00001 Loss 0.0113 (0.0230) Prec@1 100.000 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [54][31/47],lr: 0.00001 Loss 0.0127 (0.0212) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [54][41/47],lr: 0.00001 Loss 0.0131 (0.0237) Prec@1 100.000 (99.848) Prec@5 100.000 (99.981)
Train Epoch: [54][47/47],lr: 0.00001 Loss 0.0250 (0.0247) Prec@1 99.057 (99.783) Prec@5 100.000 (99.983)
Val Epoch: [54][1/46] Loss 0.6502 (0.6502)
Cls@1:0.812 Cls@5:0.969
Loc@1:0.742 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [54][11/46] Loss 0.6187 (0.8088)
Cls@1:0.789 Cls@5:0.952
Loc@1:0.661 Loc@5:0.799 Loc_gt:0.839

Val Epoch: [54][21/46] Loss 0.5860 (0.7612)
Cls@1:0.805 Cls@5:0.952
Loc@1:0.695 Loc@5:0.821 Loc_gt:0.862

Val Epoch: [54][31/46] Loss 1.2481 (0.8667)
Cls@1:0.787 Cls@5:0.940
Loc@1:0.675 Loc@5:0.804 Loc_gt:0.853

Val Epoch: [54][41/46] Loss 0.9503 (0.8520)
Cls@1:0.793 Cls@5:0.942
Loc@1:0.673 Loc@5:0.800 Loc_gt:0.845

Val Epoch: [54][46/46] Loss 0.1902 (0.8207)
Cls@1:0.802 Cls@5:0.944
Loc@1:0.682 Loc@5:0.803 Loc_gt:0.846

wrong_details:3950 1146 0 596 98 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-23
Train Epoch: [55][1/47],lr: 0.00001 Loss 0.0453 (0.0453) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [55][11/47],lr: 0.00001 Loss 0.0143 (0.0261) Prec@1 100.000 (99.716) Prec@5 100.000 (99.929)
Train Epoch: [55][21/47],lr: 0.00001 Loss 0.0123 (0.0233) Prec@1 100.000 (99.814) Prec@5 100.000 (99.963)
Train Epoch: [55][31/47],lr: 0.00001 Loss 0.0227 (0.0237) Prec@1 100.000 (99.824) Prec@5 100.000 (99.975)
Train Epoch: [55][41/47],lr: 0.00001 Loss 0.0088 (0.0222) Prec@1 100.000 (99.848) Prec@5 100.000 (99.981)
Train Epoch: [55][47/47],lr: 0.00001 Loss 0.0305 (0.0233) Prec@1 99.057 (99.800) Prec@5 100.000 (99.983)
Val Epoch: [55][1/46] Loss 0.6469 (0.6469)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [55][11/46] Loss 0.6323 (0.8140)
Cls@1:0.787 Cls@5:0.952
Loc@1:0.656 Loc@5:0.796 Loc_gt:0.835

Val Epoch: [55][21/46] Loss 0.5883 (0.7622)
Cls@1:0.807 Cls@5:0.953
Loc@1:0.696 Loc@5:0.821 Loc_gt:0.860

Val Epoch: [55][31/46] Loss 1.2256 (0.8681)
Cls@1:0.789 Cls@5:0.941
Loc@1:0.673 Loc@5:0.802 Loc_gt:0.849

Val Epoch: [55][41/46] Loss 0.9596 (0.8521)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.672 Loc@5:0.797 Loc_gt:0.841

Val Epoch: [55][46/46] Loss 0.2066 (0.8214)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.680 Loc@5:0.800 Loc_gt:0.842

wrong_details:3940 1135 0 621 93 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-24
Train Epoch: [56][1/47],lr: 0.00001 Loss 0.0223 (0.0223) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [56][11/47],lr: 0.00001 Loss 0.0123 (0.0176) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [56][21/47],lr: 0.00001 Loss 0.0164 (0.0228) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [56][31/47],lr: 0.00001 Loss 0.0070 (0.0261) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [56][41/47],lr: 0.00001 Loss 0.0100 (0.0256) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [56][47/47],lr: 0.00001 Loss 0.0191 (0.0265) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [56][1/46] Loss 0.6589 (0.6589)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.758 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [56][11/46] Loss 0.6356 (0.8184)
Cls@1:0.792 Cls@5:0.952
Loc@1:0.661 Loc@5:0.795 Loc_gt:0.834

Val Epoch: [56][21/46] Loss 0.5875 (0.7639)
Cls@1:0.810 Cls@5:0.954
Loc@1:0.698 Loc@5:0.820 Loc_gt:0.858

Val Epoch: [56][31/46] Loss 1.2358 (0.8680)
Cls@1:0.790 Cls@5:0.941
Loc@1:0.675 Loc@5:0.802 Loc_gt:0.849

Val Epoch: [56][41/46] Loss 0.9608 (0.8518)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.674 Loc@5:0.798 Loc_gt:0.842

Val Epoch: [56][46/46] Loss 0.1977 (0.8209)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.681 Loc@5:0.801 Loc_gt:0.843

wrong_details:3945 1134 0 616 94 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-25
Train Epoch: [57][1/47],lr: 0.00001 Loss 0.0228 (0.0228) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [57][11/47],lr: 0.00001 Loss 0.0200 (0.0191) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [57][21/47],lr: 0.00001 Loss 0.0162 (0.0183) Prec@1 100.000 (99.963) Prec@5 100.000 (100.000)
Train Epoch: [57][31/47],lr: 0.00001 Loss 0.0104 (0.0184) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [57][41/47],lr: 0.00001 Loss 0.0248 (0.0189) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [57][47/47],lr: 0.00001 Loss 0.0060 (0.0190) Prec@1 100.000 (99.917) Prec@5 100.000 (100.000)
Val Epoch: [57][1/46] Loss 0.6590 (0.6590)
Cls@1:0.828 Cls@5:0.969
Loc@1:0.758 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [57][11/46] Loss 0.6320 (0.8203)
Cls@1:0.792 Cls@5:0.953
Loc@1:0.662 Loc@5:0.796 Loc_gt:0.835

Val Epoch: [57][21/46] Loss 0.5810 (0.7634)
Cls@1:0.809 Cls@5:0.954
Loc@1:0.699 Loc@5:0.821 Loc_gt:0.859

Val Epoch: [57][31/46] Loss 1.2115 (0.8678)
Cls@1:0.791 Cls@5:0.942
Loc@1:0.677 Loc@5:0.802 Loc_gt:0.849

Val Epoch: [57][41/46] Loss 0.9938 (0.8541)
Cls@1:0.797 Cls@5:0.943
Loc@1:0.676 Loc@5:0.799 Loc_gt:0.843

Val Epoch: [57][46/46] Loss 0.1722 (0.8236)
Cls@1:0.805 Cls@5:0.945
Loc@1:0.683 Loc@5:0.802 Loc_gt:0.844

wrong_details:3955 1132 0 609 93 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-26
Train Epoch: [58][1/47],lr: 0.00001 Loss 0.0292 (0.0292) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [58][11/47],lr: 0.00001 Loss 0.0045 (0.0205) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [58][21/47],lr: 0.00001 Loss 0.0302 (0.0243) Prec@1 99.219 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [58][31/47],lr: 0.00001 Loss 0.0173 (0.0229) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [58][41/47],lr: 0.00001 Loss 0.0101 (0.0230) Prec@1 100.000 (99.829) Prec@5 100.000 (100.000)
Train Epoch: [58][47/47],lr: 0.00001 Loss 0.0101 (0.0224) Prec@1 100.000 (99.816) Prec@5 100.000 (100.000)
Val Epoch: [58][1/46] Loss 0.6509 (0.6509)
Cls@1:0.820 Cls@5:0.961
Loc@1:0.750 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [58][11/46] Loss 0.6303 (0.8103)
Cls@1:0.794 Cls@5:0.955
Loc@1:0.668 Loc@5:0.804 Loc_gt:0.841

Val Epoch: [58][21/46] Loss 0.5778 (0.7584)
Cls@1:0.810 Cls@5:0.955
Loc@1:0.700 Loc@5:0.824 Loc_gt:0.862

Val Epoch: [58][31/46] Loss 1.2338 (0.8663)
Cls@1:0.791 Cls@5:0.943
Loc@1:0.677 Loc@5:0.805 Loc_gt:0.851

Val Epoch: [58][41/46] Loss 0.9928 (0.8521)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.675 Loc@5:0.800 Loc_gt:0.844

Val Epoch: [58][46/46] Loss 0.1579 (0.8223)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.682 Loc@5:0.802 Loc_gt:0.845

wrong_details:3953 1132 0 608 96 5
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-27
Train Epoch: [59][1/47],lr: 0.00001 Loss 0.0184 (0.0184) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [59][11/47],lr: 0.00001 Loss 0.0147 (0.0174) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [59][21/47],lr: 0.00001 Loss 0.0201 (0.0149) Prec@1 100.000 (99.963) Prec@5 100.000 (100.000)
Train Epoch: [59][31/47],lr: 0.00001 Loss 0.0162 (0.0176) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [59][41/47],lr: 0.00001 Loss 0.0196 (0.0168) Prec@1 100.000 (99.943) Prec@5 100.000 (100.000)
Train Epoch: [59][47/47],lr: 0.00001 Loss 0.0121 (0.0198) Prec@1 100.000 (99.917) Prec@5 100.000 (100.000)
Val Epoch: [59][1/46] Loss 0.6760 (0.6760)
Cls@1:0.812 Cls@5:0.961
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.930

Val Epoch: [59][11/46] Loss 0.6409 (0.8124)
Cls@1:0.795 Cls@5:0.953
Loc@1:0.670 Loc@5:0.803 Loc_gt:0.844

Val Epoch: [59][21/46] Loss 0.5784 (0.7593)
Cls@1:0.810 Cls@5:0.954
Loc@1:0.701 Loc@5:0.825 Loc_gt:0.864

Val Epoch: [59][31/46] Loss 1.2390 (0.8683)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.676 Loc@5:0.805 Loc_gt:0.851

Val Epoch: [59][41/46] Loss 0.9909 (0.8518)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.677 Loc@5:0.802 Loc_gt:0.846

Val Epoch: [59][46/46] Loss 0.1769 (0.8225)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.683 Loc@5:0.804 Loc_gt:0.846

wrong_details:3959 1132 0 606 93 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-28
Train Epoch: [60][1/47],lr: 0.00000 Loss 0.0072 (0.0072) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [60][11/47],lr: 0.00000 Loss 0.0081 (0.0272) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [60][21/47],lr: 0.00000 Loss 0.0261 (0.0287) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [60][31/47],lr: 0.00000 Loss 0.0217 (0.0245) Prec@1 100.000 (99.899) Prec@5 100.000 (100.000)
Train Epoch: [60][41/47],lr: 0.00000 Loss 0.0154 (0.0226) Prec@1 100.000 (99.905) Prec@5 100.000 (100.000)
Train Epoch: [60][47/47],lr: 0.00000 Loss 0.0398 (0.0232) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [60][1/46] Loss 0.6739 (0.6739)
Cls@1:0.812 Cls@5:0.961
Loc@1:0.742 Loc@5:0.891 Loc_gt:0.930

Val Epoch: [60][11/46] Loss 0.6416 (0.8111)
Cls@1:0.795 Cls@5:0.953
Loc@1:0.670 Loc@5:0.803 Loc_gt:0.844

Val Epoch: [60][21/46] Loss 0.5756 (0.7582)
Cls@1:0.808 Cls@5:0.954
Loc@1:0.700 Loc@5:0.825 Loc_gt:0.864

Val Epoch: [60][31/46] Loss 1.2396 (0.8675)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.677 Loc@5:0.805 Loc_gt:0.852

Val Epoch: [60][41/46] Loss 0.9910 (0.8512)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.677 Loc@5:0.802 Loc_gt:0.846

Val Epoch: [60][46/46] Loss 0.1768 (0.8218)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.683 Loc@5:0.804 Loc_gt:0.847

wrong_details:3960 1135 0 603 92 4
Best GT_LOC: 0.8636520538488092
Best TOP1_LOC: 0.8636520538488092
2021-09-07-20-29

[vasgaowei]

Hi, the log seems all right. I have three questions:

1. First you can try our pretrained model to test the localization accuracy.
2. May I know the environment, e.g. pytorch vision and cuda version.
3. On CUB dataset, how many GPU cards do you use? My experiment on CUB dataset is carried out on one GPU card. So you can try run code on just one GPU.

[vasgaowei]

The following is my training log:
{'BASIC': {'BACKUP_CODES': True,
'BACKUP_LIST': ['lib', 'tools_cam', 'configs'],
'DISP_FREQ': 10,
'GPU_ID': [0],
'NUM_WORKERS': 40,
'ROOT_DIR': './tools_cam/..',
'SAVE_DIR': 'ckpt/CUB/deit_tscam_small_patch16_224_CAM-NORMAL_SEED26_CAM-THR0.1_BS128_2021-07-29-18-30',
'SEED': 26,
'TIME': '2021-07-29-18-30'},
'CUDNN': {'BENCHMARK': False, 'DETERMINISTIC': True, 'ENABLE': True},
'DATA': {'CROP_SIZE': 224,
'DATADIR': 'data/CUB_200_2011',
'DATASET': 'CUB',
'IMAGE_MEAN': [0.485, 0.456, 0.406],
'IMAGE_STD': [0.229, 0.224, 0.225],
'NUM_CLASSES': 200,
'RESIZE_SIZE': 256,
'SCALE_LENGTH': 15,
'SCALE_SIZE': 196},
'MODEL': {'ARCH': 'deit_tscam_small_patch16_224',
'CAM_THR': 0.1,
'LOCALIZER_DIR': '',
'TOP_K': 1},
'SOLVER': {'LR_FACTOR': 0.1,
'LR_STEPS': [30],
'MUMENTUM': 0.9,
'NUM_EPOCHS': 60,
'START_LR': 0.001,
'WEIGHT_DECAY': 0.0005},
'TEST': {'BATCH_SIZE': 128,
'CKPT_DIR': '',
'SAVE_BOXED_IMAGE': False,
'SAVE_CAMS': False,
'TEN_CROPS': False},
'TRAIN': {'ALPHA': 1.0, 'BATCH_SIZE': 128, 'BETA': 1.0}}
==> Preparing data...
done!
==> Preparing networks for baseline...
Removing key head.weight from pretrained checkpoint
Removing key head.bias from pretrained checkpoint
TSCAM(
(patch_embed): PatchEmbed(
(proj): Conv2d(3, 384, kernel_size=(16, 16), stride=(16, 16))
)
(pos_drop): Dropout(p=0.0, inplace=False)
(blocks): ModuleList(
(0): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): Identity()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(1): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(2): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(3): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(4): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(5): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(6): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(7): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(8): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(9): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(10): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
(11): Block(
(norm1): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(attn): Attention(
(qkv): Linear(in_features=384, out_features=1152, bias=True)
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=384, out_features=384, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(drop_path): DropPath()
(norm2): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(mlp): Mlp(
(fc1): Linear(in_features=384, out_features=1536, bias=True)
(act): GELU()
(fc2): Linear(in_features=1536, out_features=384, bias=True)
(drop): Dropout(p=0.0, inplace=False)
)
)
)
(norm): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
(head): Conv2d(384, 200, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(avgpool): AdaptiveAvgPool2d(output_size=1)
)
Preparing networks done!
Train Epoch: [1][1/47],lr: 0.00005 Loss 5.3975 (5.3975) Prec@1 0.781 (0.781) Prec@5 2.344 (2.344)
Train Epoch: [1][11/47],lr: 0.00005 Loss 5.2529 (5.3262) Prec@1 3.906 (1.136) Prec@5 6.250 (3.622)
Train Epoch: [1][21/47],lr: 0.00005 Loss 5.1997 (5.2758) Prec@1 3.125 (1.451) Prec@5 7.812 (5.171)
Train Epoch: [1][31/47],lr: 0.00005 Loss 4.9600 (5.2138) Prec@1 4.688 (1.865) Prec@5 17.969 (7.283)
Train Epoch: [1][41/47],lr: 0.00005 Loss 4.6716 (5.1099) Prec@1 7.812 (3.316) Prec@5 22.656 (11.414)
Train Epoch: [1][47/47],lr: 0.00005 Loss 4.4518 (5.0362) Prec@1 13.208 (4.154) Prec@5 27.358 (13.714)
Val Epoch: [1][1/46] Loss 3.7797 (3.7797)
Cls@1:0.406 Cls@5:0.695
Loc@1:0.297 Loc@5:0.531 Loc_gt:0.742

Val Epoch: [1][11/46] Loss 3.6077 (4.2400)
Cls@1:0.200 Cls@5:0.433
Loc@1:0.134 Loc@5:0.274 Loc_gt:0.503

Val Epoch: [1][21/46] Loss 4.4082 (4.1473)
Cls@1:0.206 Cls@5:0.478
Loc@1:0.145 Loc@5:0.319 Loc_gt:0.534

Val Epoch: [1][31/46] Loss 4.7425 (4.2340)
Cls@1:0.180 Cls@5:0.433
Loc@1:0.129 Loc@5:0.288 Loc_gt:0.501

Val Epoch: [1][41/46] Loss 4.1821 (4.2075)
Cls@1:0.163 Cls@5:0.427
Loc@1:0.115 Loc@5:0.283 Loc_gt:0.520

Val Epoch: [1][46/46] Loss 3.8226 (4.2142)
Cls@1:0.171 Cls@5:0.438
Loc@1:0.118 Loc@5:0.284 Loc_gt:0.510

wrong_details:685 4804 0 84 217 4
Best GT_LOC: 0.5101829478771143
Best TOP1_LOC: 0.5101829478771143
2021-07-29-18-34
Train Epoch: [2][1/47],lr: 0.00005 Loss 4.2093 (4.2093) Prec@1 15.625 (15.625) Prec@5 47.656 (47.656)
Train Epoch: [2][11/47],lr: 0.00005 Loss 3.7600 (4.0016) Prec@1 22.656 (24.148) Prec@5 55.469 (55.185)
Train Epoch: [2][21/47],lr: 0.00005 Loss 3.4648 (3.8098) Prec@1 31.250 (26.637) Prec@5 65.625 (58.482)
Train Epoch: [2][31/47],lr: 0.00005 Loss 3.1710 (3.6248) Prec@1 36.719 (29.612) Prec@5 67.969 (62.021)
Train Epoch: [2][41/47],lr: 0.00005 Loss 2.9165 (3.4513) Prec@1 40.625 (33.194) Prec@5 72.656 (64.958)
Train Epoch: [2][47/47],lr: 0.00005 Loss 2.7606 (3.3669) Prec@1 45.283 (34.768) Prec@5 73.585 (66.333)
Val Epoch: [2][1/46] Loss 2.3769 (2.3769)
Cls@1:0.469 Cls@5:0.875
Loc@1:0.445 Loc@5:0.812 Loc_gt:0.922

Val Epoch: [2][11/46] Loss 2.1869 (2.3382)
Cls@1:0.496 Cls@5:0.827
Loc@1:0.434 Loc@5:0.715 Loc_gt:0.858

Val Epoch: [2][21/46] Loss 2.4960 (2.2341)
Cls@1:0.542 Cls@5:0.847
Loc@1:0.476 Loc@5:0.742 Loc_gt:0.864

Val Epoch: [2][31/46] Loss 2.9898 (2.3796)
Cls@1:0.503 Cls@5:0.817
Loc@1:0.439 Loc@5:0.709 Loc_gt:0.852

Val Epoch: [2][41/46] Loss 3.0186 (2.4237)
Cls@1:0.490 Cls@5:0.814
Loc@1:0.424 Loc@5:0.701 Loc_gt:0.845

Val Epoch: [2][46/46] Loss 3.2198 (2.3986)
Cls@1:0.506 Cls@5:0.818
Loc@1:0.438 Loc@5:0.706 Loc_gt:0.846

wrong_details:2535 2864 0 292 99 4
Best GT_LOC: 0.8458750431480843
Best TOP1_LOC: 0.8458750431480843
2021-07-29-18-38
Train Epoch: [3][1/47],lr: 0.00005 Loss 2.4513 (2.4513) Prec@1 58.594 (58.594) Prec@5 86.719 (86.719)
Train Epoch: [3][11/47],lr: 0.00005 Loss 2.3828 (2.3546) Prec@1 60.156 (57.812) Prec@5 85.156 (86.151)
Train Epoch: [3][21/47],lr: 0.00005 Loss 2.2079 (2.2594) Prec@1 56.250 (58.445) Prec@5 83.594 (86.570)
Train Epoch: [3][31/47],lr: 0.00005 Loss 1.8676 (2.1664) Prec@1 63.281 (60.030) Prec@5 89.844 (87.374)
Train Epoch: [3][41/47],lr: 0.00005 Loss 1.6491 (2.0878) Prec@1 74.219 (61.338) Prec@5 92.188 (87.976)
Train Epoch: [3][47/47],lr: 0.00005 Loss 1.7702 (2.0413) Prec@1 68.868 (62.196) Prec@5 93.396 (88.488)
Val Epoch: [3][1/46] Loss 1.6008 (1.6008)
Cls@1:0.719 Cls@5:0.938
Loc@1:0.664 Loc@5:0.875 Loc_gt:0.922

Val Epoch: [3][11/46] Loss 1.4895 (1.5467)
Cls@1:0.661 Cls@5:0.903
Loc@1:0.588 Loc@5:0.801 Loc_gt:0.884

Val Epoch: [3][21/46] Loss 1.5027 (1.4481)
Cls@1:0.681 Cls@5:0.913
Loc@1:0.612 Loc@5:0.818 Loc_gt:0.892

Val Epoch: [3][31/46] Loss 1.9508 (1.6030)
Cls@1:0.646 Cls@5:0.893
Loc@1:0.576 Loc@5:0.796 Loc_gt:0.885

Val Epoch: [3][41/46] Loss 2.1058 (1.6386)
Cls@1:0.638 Cls@5:0.897
Loc@1:0.566 Loc@5:0.794 Loc_gt:0.878

Val Epoch: [3][46/46] Loss 1.4461 (1.6035)
Cls@1:0.653 Cls@5:0.901
Loc@1:0.579 Loc@5:0.798 Loc_gt:0.877

wrong_details:3356 2013 0 333 89 3
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-18-43
Train Epoch: [4][1/47],lr: 0.00005 Loss 1.4204 (1.4204) Prec@1 79.688 (79.688) Prec@5 94.531 (94.531)
Train Epoch: [4][11/47],lr: 0.00005 Loss 1.5755 (1.4380) Prec@1 72.656 (76.065) Prec@5 92.188 (94.957)
Train Epoch: [4][21/47],lr: 0.00005 Loss 1.3673 (1.4091) Prec@1 77.344 (76.265) Prec@5 92.969 (94.717)
Train Epoch: [4][31/47],lr: 0.00005 Loss 1.2662 (1.3627) Prec@1 78.125 (76.210) Prec@5 96.094 (94.708)
Train Epoch: [4][41/47],lr: 0.00005 Loss 1.2686 (1.3347) Prec@1 75.000 (76.258) Prec@5 95.312 (95.065)
Train Epoch: [4][47/47],lr: 0.00005 Loss 1.2410 (1.3140) Prec@1 75.472 (76.577) Prec@5 94.340 (95.078)
Val Epoch: [4][1/46] Loss 1.2665 (1.2665)
Cls@1:0.719 Cls@5:0.953
Loc@1:0.633 Loc@5:0.852 Loc_gt:0.898

Val Epoch: [4][11/46] Loss 1.1409 (1.2055)
Cls@1:0.720 Cls@5:0.930
Loc@1:0.614 Loc@5:0.791 Loc_gt:0.847

Val Epoch: [4][21/46] Loss 1.1160 (1.1277)
Cls@1:0.740 Cls@5:0.932
Loc@1:0.643 Loc@5:0.811 Loc_gt:0.867

Val Epoch: [4][31/46] Loss 1.6061 (1.2480)
Cls@1:0.708 Cls@5:0.921
Loc@1:0.604 Loc@5:0.785 Loc_gt:0.850

Val Epoch: [4][41/46] Loss 1.5609 (1.2522)
Cls@1:0.712 Cls@5:0.925
Loc@1:0.599 Loc@5:0.780 Loc_gt:0.841

Val Epoch: [4][46/46] Loss 0.8346 (1.2183)
Cls@1:0.723 Cls@5:0.928
Loc@1:0.609 Loc@5:0.784 Loc_gt:0.842

wrong_details:3531 1605 0 596 60 2
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-18-45
Train Epoch: [5][1/47],lr: 0.00005 Loss 0.9986 (0.9986) Prec@1 80.469 (80.469) Prec@5 98.438 (98.438)
Train Epoch: [5][11/47],lr: 0.00005 Loss 0.9564 (0.9716) Prec@1 83.594 (84.091) Prec@5 96.875 (97.230)
Train Epoch: [5][21/47],lr: 0.00005 Loss 0.9577 (0.9841) Prec@1 82.812 (83.259) Prec@5 97.656 (97.247)
Train Epoch: [5][31/47],lr: 0.00005 Loss 0.9741 (0.9774) Prec@1 81.250 (82.812) Prec@5 95.312 (97.228)
Train Epoch: [5][41/47],lr: 0.00005 Loss 0.9631 (0.9640) Prec@1 81.250 (83.041) Prec@5 97.656 (97.275)
Train Epoch: [5][47/47],lr: 0.00005 Loss 1.0138 (0.9557) Prec@1 75.472 (82.799) Prec@5 97.170 (97.297)
Val Epoch: [5][1/46] Loss 1.0437 (1.0437)
Cls@1:0.773 Cls@5:0.953
Loc@1:0.711 Loc@5:0.883 Loc_gt:0.922

Val Epoch: [5][11/46] Loss 0.8476 (1.0675)
Cls@1:0.726 Cls@5:0.935
Loc@1:0.639 Loc@5:0.825 Loc_gt:0.881

Val Epoch: [5][21/46] Loss 0.8469 (0.9897)
Cls@1:0.751 Cls@5:0.940
Loc@1:0.673 Loc@5:0.844 Loc_gt:0.892

Val Epoch: [5][31/46] Loss 1.3697 (1.0892)
Cls@1:0.731 Cls@5:0.928
Loc@1:0.650 Loc@5:0.830 Loc_gt:0.886

Val Epoch: [5][41/46] Loss 1.2690 (1.0804)
Cls@1:0.737 Cls@5:0.932
Loc@1:0.651 Loc@5:0.825 Loc_gt:0.877

Val Epoch: [5][46/46] Loss 0.7160 (1.0521)
Cls@1:0.746 Cls@5:0.935
Loc@1:0.659 Loc@5:0.827 Loc_gt:0.877

wrong_details:3817 1474 0 418 83 2
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-18-50
Train Epoch: [6][1/47],lr: 0.00005 Loss 0.7829 (0.7829) Prec@1 87.500 (87.500) Prec@5 99.219 (99.219)
Train Epoch: [6][11/47],lr: 0.00005 Loss 0.7212 (0.7400) Prec@1 87.500 (87.571) Prec@5 96.875 (98.509)
Train Epoch: [6][21/47],lr: 0.00005 Loss 0.6827 (0.7170) Prec@1 87.500 (87.723) Prec@5 99.219 (98.586)
Train Epoch: [6][31/47],lr: 0.00005 Loss 0.6239 (0.7131) Prec@1 89.062 (87.273) Prec@5 96.875 (98.488)
Train Epoch: [6][41/47],lr: 0.00005 Loss 0.6152 (0.7087) Prec@1 89.844 (87.119) Prec@5 97.656 (98.438)
Train Epoch: [6][47/47],lr: 0.00005 Loss 0.6992 (0.7071) Prec@1 87.736 (86.954) Prec@5 98.113 (98.398)
Val Epoch: [6][1/46] Loss 0.9131 (0.9131)
Cls@1:0.812 Cls@5:0.961
Loc@1:0.758 Loc@5:0.891 Loc_gt:0.930

Val Epoch: [6][11/46] Loss 0.7854 (0.9285)
Cls@1:0.752 Cls@5:0.952
Loc@1:0.656 Loc@5:0.831 Loc_gt:0.873

Val Epoch: [6][21/46] Loss 0.8043 (0.8667)
Cls@1:0.776 Cls@5:0.951
Loc@1:0.689 Loc@5:0.847 Loc_gt:0.890

Val Epoch: [6][31/46] Loss 1.2412 (0.9676)
Cls@1:0.750 Cls@5:0.938
Loc@1:0.663 Loc@5:0.831 Loc_gt:0.881

Val Epoch: [6][41/46] Loss 1.0796 (0.9628)
Cls@1:0.751 Cls@5:0.941
Loc@1:0.656 Loc@5:0.824 Loc_gt:0.869

Val Epoch: [6][46/46] Loss 0.4715 (0.9322)
Cls@1:0.761 Cls@5:0.944
Loc@1:0.664 Loc@5:0.825 Loc_gt:0.868

wrong_details:3847 1384 0 475 85 3
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-18-52
Train Epoch: [7][1/47],lr: 0.00005 Loss 0.6169 (0.6169) Prec@1 89.844 (89.844) Prec@5 98.438 (98.438)
Train Epoch: [7][11/47],lr: 0.00005 Loss 0.5575 (0.5960) Prec@1 95.312 (90.199) Prec@5 100.000 (98.722)
Train Epoch: [7][21/47],lr: 0.00005 Loss 0.4567 (0.5803) Prec@1 92.188 (89.993) Prec@5 99.219 (98.735)
Train Epoch: [7][31/47],lr: 0.00005 Loss 0.4082 (0.5770) Prec@1 94.531 (89.919) Prec@5 100.000 (98.765)
Train Epoch: [7][41/47],lr: 0.00005 Loss 0.4784 (0.5590) Prec@1 92.969 (90.282) Prec@5 99.219 (98.895)
Train Epoch: [7][47/47],lr: 0.00005 Loss 0.4825 (0.5620) Prec@1 92.453 (90.157) Prec@5 97.170 (98.832)
Val Epoch: [7][1/46] Loss 0.8726 (0.8726)
Cls@1:0.812 Cls@5:0.945
Loc@1:0.750 Loc@5:0.883 Loc_gt:0.930

Val Epoch: [7][11/46] Loss 0.6915 (0.8627)
Cls@1:0.769 Cls@5:0.950
Loc@1:0.665 Loc@5:0.826 Loc_gt:0.866

Val Epoch: [7][21/46] Loss 0.7847 (0.8110)
Cls@1:0.784 Cls@5:0.951
Loc@1:0.696 Loc@5:0.846 Loc_gt:0.886

Val Epoch: [7][31/46] Loss 1.4040 (0.9138)
Cls@1:0.757 Cls@5:0.937
Loc@1:0.670 Loc@5:0.829 Loc_gt:0.879

Val Epoch: [7][41/46] Loss 1.1045 (0.9002)
Cls@1:0.762 Cls@5:0.940
Loc@1:0.669 Loc@5:0.825 Loc_gt:0.870

Val Epoch: [7][46/46] Loss 0.4902 (0.8751)
Cls@1:0.770 Cls@5:0.942
Loc@1:0.675 Loc@5:0.826 Loc_gt:0.870

wrong_details:3911 1331 0 463 87 2
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-18-56
Train Epoch: [8][1/47],lr: 0.00005 Loss 0.4312 (0.4312) Prec@1 92.969 (92.969) Prec@5 100.000 (100.000)
Train Epoch: [8][11/47],lr: 0.00005 Loss 0.4584 (0.4660) Prec@1 90.625 (91.974) Prec@5 100.000 (99.432)
Train Epoch: [8][21/47],lr: 0.00005 Loss 0.5042 (0.4616) Prec@1 94.531 (92.336) Prec@5 98.438 (99.405)
Train Epoch: [8][31/47],lr: 0.00005 Loss 0.3665 (0.4568) Prec@1 92.969 (92.364) Prec@5 99.219 (99.269)
Train Epoch: [8][41/47],lr: 0.00005 Loss 0.3789 (0.4555) Prec@1 93.750 (92.168) Prec@5 100.000 (99.257)
Train Epoch: [8][47/47],lr: 0.00005 Loss 0.4894 (0.4515) Prec@1 89.623 (92.159) Prec@5 98.113 (99.283)
Val Epoch: [8][1/46] Loss 0.7461 (0.7461)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.750 Loc@5:0.898 Loc_gt:0.914

Val Epoch: [8][11/46] Loss 0.6860 (0.8267)
Cls@1:0.772 Cls@5:0.951
Loc@1:0.676 Loc@5:0.834 Loc_gt:0.874

Val Epoch: [8][21/46] Loss 0.8028 (0.7804)
Cls@1:0.789 Cls@5:0.953
Loc@1:0.707 Loc@5:0.853 Loc_gt:0.892

Val Epoch: [8][31/46] Loss 1.2213 (0.8680)
Cls@1:0.767 Cls@5:0.942
Loc@1:0.685 Loc@5:0.839 Loc_gt:0.884

Val Epoch: [8][41/46] Loss 0.9572 (0.8582)
Cls@1:0.773 Cls@5:0.944
Loc@1:0.685 Loc@5:0.835 Loc_gt:0.877

Val Epoch: [8][46/46] Loss 0.3698 (0.8313)
Cls@1:0.783 Cls@5:0.947
Loc@1:0.693 Loc@5:0.837 Loc_gt:0.877

wrong_details:4017 1259 0 404 111 3
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-19-00
Train Epoch: [9][1/47],lr: 0.00005 Loss 0.3265 (0.3265) Prec@1 93.750 (93.750) Prec@5 99.219 (99.219)
Train Epoch: [9][11/47],lr: 0.00005 Loss 0.3712 (0.3404) Prec@1 96.094 (94.531) Prec@5 98.438 (99.716)
Train Epoch: [9][21/47],lr: 0.00005 Loss 0.3422 (0.3583) Prec@1 94.531 (94.159) Prec@5 100.000 (99.777)
Train Epoch: [9][31/47],lr: 0.00005 Loss 0.4820 (0.3699) Prec@1 92.188 (94.027) Prec@5 100.000 (99.798)
Train Epoch: [9][41/47],lr: 0.00005 Loss 0.4142 (0.3615) Prec@1 90.625 (94.322) Prec@5 99.219 (99.809)
Train Epoch: [9][47/47],lr: 0.00005 Loss 0.4600 (0.3638) Prec@1 93.396 (94.261) Prec@5 100.000 (99.783)
Val Epoch: [9][1/46] Loss 0.7365 (0.7365)
Cls@1:0.812 Cls@5:0.961
Loc@1:0.727 Loc@5:0.867 Loc_gt:0.891

Val Epoch: [9][11/46] Loss 0.6041 (0.8104)
Cls@1:0.767 Cls@5:0.943
Loc@1:0.660 Loc@5:0.813 Loc_gt:0.858

Val Epoch: [9][21/46] Loss 0.6847 (0.7489)
Cls@1:0.791 Cls@5:0.948
Loc@1:0.698 Loc@5:0.836 Loc_gt:0.878

Val Epoch: [9][31/46] Loss 1.1688 (0.8474)
Cls@1:0.768 Cls@5:0.936
Loc@1:0.675 Loc@5:0.820 Loc_gt:0.872

Val Epoch: [9][41/46] Loss 0.9201 (0.8349)
Cls@1:0.775 Cls@5:0.940
Loc@1:0.675 Loc@5:0.818 Loc_gt:0.865

Val Epoch: [9][46/46] Loss 0.4047 (0.8100)
Cls@1:0.784 Cls@5:0.943
Loc@1:0.684 Loc@5:0.821 Loc_gt:0.865

wrong_details:3964 1253 0 476 99 2
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-19-03
Train Epoch: [10][1/47],lr: 0.00005 Loss 0.2180 (0.2180) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [10][11/47],lr: 0.00005 Loss 0.3298 (0.2817) Prec@1 95.312 (96.165) Prec@5 100.000 (99.858)
Train Epoch: [10][21/47],lr: 0.00005 Loss 0.2394 (0.2929) Prec@1 98.438 (95.722) Prec@5 100.000 (99.740)
Train Epoch: [10][31/47],lr: 0.00005 Loss 0.2720 (0.2980) Prec@1 96.094 (95.766) Prec@5 99.219 (99.723)
Train Epoch: [10][41/47],lr: 0.00005 Loss 0.3784 (0.2990) Prec@1 92.188 (95.446) Prec@5 97.656 (99.676)
Train Epoch: [10][47/47],lr: 0.00005 Loss 0.2965 (0.3023) Prec@1 94.340 (95.295) Prec@5 100.000 (99.700)
Val Epoch: [10][1/46] Loss 0.7922 (0.7922)
Cls@1:0.828 Cls@5:0.961
Loc@1:0.758 Loc@5:0.883 Loc_gt:0.898

Val Epoch: [10][11/46] Loss 0.6755 (0.8129)
Cls@1:0.767 Cls@5:0.948
Loc@1:0.665 Loc@5:0.826 Loc_gt:0.866

Val Epoch: [10][21/46] Loss 0.6103 (0.7461)
Cls@1:0.791 Cls@5:0.952
Loc@1:0.703 Loc@5:0.846 Loc_gt:0.884

Val Epoch: [10][31/46] Loss 1.2216 (0.8457)
Cls@1:0.769 Cls@5:0.940
Loc@1:0.684 Loc@5:0.835 Loc_gt:0.883

Val Epoch: [10][41/46] Loss 1.1595 (0.8359)
Cls@1:0.774 Cls@5:0.942
Loc@1:0.684 Loc@5:0.832 Loc_gt:0.877

Val Epoch: [10][46/46] Loss 0.4607 (0.8122)
Cls@1:0.782 Cls@5:0.945
Loc@1:0.691 Loc@5:0.833 Loc_gt:0.876

wrong_details:4005 1261 0 418 107 3
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-19-08
Train Epoch: [11][1/47],lr: 0.00005 Loss 0.2088 (0.2088) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [11][11/47],lr: 0.00005 Loss 0.2020 (0.2454) Prec@1 96.875 (96.591) Prec@5 100.000 (99.716)
Train Epoch: [11][21/47],lr: 0.00005 Loss 0.2109 (0.2417) Prec@1 98.438 (96.615) Prec@5 100.000 (99.777)
Train Epoch: [11][31/47],lr: 0.00005 Loss 0.2429 (0.2433) Prec@1 98.438 (96.623) Prec@5 100.000 (99.824)
Train Epoch: [11][41/47],lr: 0.00005 Loss 0.2258 (0.2456) Prec@1 96.875 (96.399) Prec@5 100.000 (99.829)
Train Epoch: [11][47/47],lr: 0.00005 Loss 0.2390 (0.2453) Prec@1 98.113 (96.396) Prec@5 100.000 (99.850)
Val Epoch: [11][1/46] Loss 0.8032 (0.8032)
Cls@1:0.820 Cls@5:0.961
Loc@1:0.750 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [11][11/46] Loss 0.6370 (0.7850)
Cls@1:0.778 Cls@5:0.946
Loc@1:0.674 Loc@5:0.817 Loc_gt:0.864

Val Epoch: [11][21/46] Loss 0.6289 (0.7285)
Cls@1:0.796 Cls@5:0.950
Loc@1:0.708 Loc@5:0.842 Loc_gt:0.886

Val Epoch: [11][31/46] Loss 1.2080 (0.8236)
Cls@1:0.772 Cls@5:0.941
Loc@1:0.686 Loc@5:0.832 Loc_gt:0.880

Val Epoch: [11][41/46] Loss 1.0575 (0.8178)
Cls@1:0.776 Cls@5:0.942
Loc@1:0.682 Loc@5:0.825 Loc_gt:0.871

Val Epoch: [11][46/46] Loss 0.3417 (0.7904)
Cls@1:0.785 Cls@5:0.945
Loc@1:0.691 Loc@5:0.828 Loc_gt:0.872

wrong_details:4003 1244 0 436 107 4
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-19-10
Train Epoch: [12][1/47],lr: 0.00005 Loss 0.3106 (0.3106) Prec@1 95.312 (95.312) Prec@5 100.000 (100.000)
Train Epoch: [12][11/47],lr: 0.00005 Loss 0.1699 (0.2051) Prec@1 100.000 (97.727) Prec@5 100.000 (100.000)
Train Epoch: [12][21/47],lr: 0.00005 Loss 0.1917 (0.2036) Prec@1 98.438 (97.693) Prec@5 100.000 (100.000)
Train Epoch: [12][31/47],lr: 0.00005 Loss 0.2584 (0.2026) Prec@1 96.875 (97.681) Prec@5 100.000 (99.950)
Train Epoch: [12][41/47],lr: 0.00005 Loss 0.1359 (0.2012) Prec@1 97.656 (97.637) Prec@5 100.000 (99.943)
Train Epoch: [12][47/47],lr: 0.00005 Loss 0.3759 (0.2064) Prec@1 96.226 (97.548) Prec@5 99.057 (99.933)
Val Epoch: [12][1/46] Loss 0.7202 (0.7202)
Cls@1:0.836 Cls@5:0.969
Loc@1:0.773 Loc@5:0.898 Loc_gt:0.914

Val Epoch: [12][11/46] Loss 0.6072 (0.7888)
Cls@1:0.776 Cls@5:0.949
Loc@1:0.678 Loc@5:0.827 Loc_gt:0.871

Val Epoch: [12][21/46] Loss 0.7211 (0.7424)
Cls@1:0.792 Cls@5:0.950
Loc@1:0.702 Loc@5:0.841 Loc_gt:0.884

Val Epoch: [12][31/46] Loss 1.1475 (0.8273)
Cls@1:0.774 Cls@5:0.941
Loc@1:0.685 Loc@5:0.832 Loc_gt:0.879

Val Epoch: [12][41/46] Loss 0.9435 (0.8154)
Cls@1:0.778 Cls@5:0.944
Loc@1:0.686 Loc@5:0.831 Loc_gt:0.875

Val Epoch: [12][46/46] Loss 0.3875 (0.7881)
Cls@1:0.787 Cls@5:0.946
Loc@1:0.695 Loc@5:0.834 Loc_gt:0.875

wrong_details:4027 1234 0 394 134 5
Best GT_LOC: 0.8774594408008285
Best TOP1_LOC: 0.8774594408008285
2021-07-29-19-15
Train Epoch: [13][1/47],lr: 0.00005 Loss 0.1637 (0.1637) Prec@1 97.656 (97.656) Prec@5 100.000 (100.000)
Train Epoch: [13][11/47],lr: 0.00005 Loss 0.2012 (0.1736) Prec@1 98.438 (98.082) Prec@5 100.000 (99.858)
Train Epoch: [13][21/47],lr: 0.00005 Loss 0.2259 (0.1743) Prec@1 96.875 (98.065) Prec@5 99.219 (99.851)
Train Epoch: [13][31/47],lr: 0.00005 Loss 0.1786 (0.1771) Prec@1 96.875 (97.833) Prec@5 100.000 (99.899)
Train Epoch: [13][41/47],lr: 0.00005 Loss 0.2009 (0.1784) Prec@1 99.219 (97.847) Prec@5 100.000 (99.905)
Train Epoch: [13][47/47],lr: 0.00005 Loss 0.2057 (0.1775) Prec@1 96.226 (97.881) Prec@5 100.000 (99.917)
Val Epoch: [13][1/46] Loss 0.6217 (0.6217)
Cls@1:0.859 Cls@5:0.969
Loc@1:0.797 Loc@5:0.906 Loc_gt:0.922

Val Epoch: [13][11/46] Loss 0.5806 (0.7972)
Cls@1:0.776 Cls@5:0.945
Loc@1:0.685 Loc@5:0.834 Loc_gt:0.879

Val Epoch: [13][21/46] Loss 0.6402 (0.7271)
Cls@1:0.799 Cls@5:0.950
Loc@1:0.717 Loc@5:0.853 Loc_gt:0.893

Val Epoch: [13][31/46] Loss 1.0860 (0.8147)
Cls@1:0.781 Cls@5:0.941
Loc@1:0.702 Loc@5:0.846 Loc_gt:0.891

Val Epoch: [13][41/46] Loss 0.9693 (0.8071)
Cls@1:0.783 Cls@5:0.944
Loc@1:0.700 Loc@5:0.844 Loc_gt:0.886

Val Epoch: [13][46/46] Loss 0.2528 (0.7803)
Cls@1:0.791 Cls@5:0.946
Loc@1:0.708 Loc@5:0.846 Loc_gt:0.886

wrong_details:4105 1209 0 342 133 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-18
Train Epoch: [14][1/47],lr: 0.00005 Loss 0.1224 (0.1224) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [14][11/47],lr: 0.00005 Loss 0.2579 (0.1445) Prec@1 96.094 (98.651) Prec@5 100.000 (100.000)
Train Epoch: [14][21/47],lr: 0.00005 Loss 0.1610 (0.1478) Prec@1 97.656 (98.549) Prec@5 100.000 (99.926)
Train Epoch: [14][31/47],lr: 0.00005 Loss 0.1278 (0.1563) Prec@1 97.656 (98.589) Prec@5 100.000 (99.849)
Train Epoch: [14][41/47],lr: 0.00005 Loss 0.1337 (0.1546) Prec@1 99.219 (98.571) Prec@5 100.000 (99.867)
Train Epoch: [14][47/47],lr: 0.00005 Loss 0.1301 (0.1538) Prec@1 97.170 (98.515) Prec@5 100.000 (99.867)
Val Epoch: [14][1/46] Loss 0.6479 (0.6479)
Cls@1:0.836 Cls@5:0.969
Loc@1:0.781 Loc@5:0.914 Loc_gt:0.938

Val Epoch: [14][11/46] Loss 0.5583 (0.7721)
Cls@1:0.783 Cls@5:0.949
Loc@1:0.685 Loc@5:0.827 Loc_gt:0.869

Val Epoch: [14][21/46] Loss 0.6617 (0.7133)
Cls@1:0.804 Cls@5:0.952
Loc@1:0.716 Loc@5:0.847 Loc_gt:0.887

Val Epoch: [14][31/46] Loss 1.0963 (0.8052)
Cls@1:0.784 Cls@5:0.943
Loc@1:0.699 Loc@5:0.839 Loc_gt:0.883

Val Epoch: [14][41/46] Loss 0.9647 (0.7952)
Cls@1:0.786 Cls@5:0.945
Loc@1:0.700 Loc@5:0.838 Loc_gt:0.880

Val Epoch: [14][46/46] Loss 0.2616 (0.7697)
Cls@1:0.794 Cls@5:0.947
Loc@1:0.706 Loc@5:0.840 Loc_gt:0.879

wrong_details:4093 1193 0 350 153 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-22
Train Epoch: [15][1/47],lr: 0.00005 Loss 0.0920 (0.0920) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [15][11/47],lr: 0.00005 Loss 0.1185 (0.1266) Prec@1 97.656 (99.077) Prec@5 100.000 (100.000)
Train Epoch: [15][21/47],lr: 0.00005 Loss 0.1587 (0.1217) Prec@1 96.094 (99.144) Prec@5 100.000 (100.000)
Train Epoch: [15][31/47],lr: 0.00005 Loss 0.1418 (0.1242) Prec@1 98.438 (98.942) Prec@5 99.219 (99.975)
Train Epoch: [15][41/47],lr: 0.00005 Loss 0.1504 (0.1277) Prec@1 98.438 (98.876) Prec@5 100.000 (99.981)
Train Epoch: [15][47/47],lr: 0.00005 Loss 0.0763 (0.1257) Prec@1 99.057 (98.916) Prec@5 100.000 (99.983)
Val Epoch: [15][1/46] Loss 0.6086 (0.6086)
Cls@1:0.867 Cls@5:0.969
Loc@1:0.781 Loc@5:0.883 Loc_gt:0.898

Val Epoch: [15][11/46] Loss 0.5905 (0.7670)
Cls@1:0.782 Cls@5:0.955
Loc@1:0.679 Loc@5:0.831 Loc_gt:0.867

Val Epoch: [15][21/46] Loss 0.7094 (0.7247)
Cls@1:0.798 Cls@5:0.954
Loc@1:0.708 Loc@5:0.846 Loc_gt:0.884

Val Epoch: [15][31/46] Loss 1.1803 (0.8207)
Cls@1:0.779 Cls@5:0.943
Loc@1:0.690 Loc@5:0.833 Loc_gt:0.878

Val Epoch: [15][41/46] Loss 0.9536 (0.8109)
Cls@1:0.784 Cls@5:0.944
Loc@1:0.690 Loc@5:0.830 Loc_gt:0.872

Val Epoch: [15][46/46] Loss 0.2946 (0.7841)
Cls@1:0.793 Cls@5:0.946
Loc@1:0.699 Loc@5:0.832 Loc_gt:0.873

wrong_details:4051 1200 0 388 151 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-26
Train Epoch: [16][1/47],lr: 0.00005 Loss 0.1091 (0.1091) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [16][11/47],lr: 0.00005 Loss 0.1076 (0.1208) Prec@1 100.000 (99.077) Prec@5 100.000 (99.929)
Train Epoch: [16][21/47],lr: 0.00005 Loss 0.2093 (0.1128) Prec@1 96.094 (98.772) Prec@5 100.000 (99.926)
Train Epoch: [16][31/47],lr: 0.00005 Loss 0.1593 (0.1130) Prec@1 96.875 (98.740) Prec@5 100.000 (99.950)
Train Epoch: [16][41/47],lr: 0.00005 Loss 0.1009 (0.1138) Prec@1 99.219 (98.819) Prec@5 100.000 (99.962)
Train Epoch: [16][47/47],lr: 0.00005 Loss 0.0971 (0.1143) Prec@1 98.113 (98.832) Prec@5 100.000 (99.967)
Val Epoch: [16][1/46] Loss 0.6149 (0.6149)
Cls@1:0.828 Cls@5:0.961
Loc@1:0.750 Loc@5:0.883 Loc_gt:0.906

Val Epoch: [16][11/46] Loss 0.5735 (0.7710)
Cls@1:0.781 Cls@5:0.952
Loc@1:0.681 Loc@5:0.828 Loc_gt:0.869

Val Epoch: [16][21/46] Loss 0.7000 (0.7289)
Cls@1:0.798 Cls@5:0.952
Loc@1:0.707 Loc@5:0.843 Loc_gt:0.885

Val Epoch: [16][31/46] Loss 1.1836 (0.8269)
Cls@1:0.776 Cls@5:0.941
Loc@1:0.687 Loc@5:0.831 Loc_gt:0.878

Val Epoch: [16][41/46] Loss 0.8843 (0.8152)
Cls@1:0.781 Cls@5:0.943
Loc@1:0.688 Loc@5:0.830 Loc_gt:0.874

Val Epoch: [16][46/46] Loss 0.2492 (0.7890)
Cls@1:0.790 Cls@5:0.945
Loc@1:0.698 Loc@5:0.833 Loc_gt:0.875

wrong_details:4043 1215 0 398 132 6
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-29
Train Epoch: [17][1/47],lr: 0.00005 Loss 0.0645 (0.0645) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [17][11/47],lr: 0.00005 Loss 0.1385 (0.1003) Prec@1 96.875 (98.366) Prec@5 100.000 (99.929)
Train Epoch: [17][21/47],lr: 0.00005 Loss 0.1319 (0.1003) Prec@1 100.000 (98.735) Prec@5 100.000 (99.963)
Train Epoch: [17][31/47],lr: 0.00005 Loss 0.1340 (0.1022) Prec@1 98.438 (98.816) Prec@5 100.000 (99.975)
Train Epoch: [17][41/47],lr: 0.00005 Loss 0.1350 (0.1045) Prec@1 98.438 (98.742) Prec@5 100.000 (99.943)
Train Epoch: [17][47/47],lr: 0.00005 Loss 0.1280 (0.1042) Prec@1 99.057 (98.815) Prec@5 100.000 (99.950)
Val Epoch: [17][1/46] Loss 0.6840 (0.6840)
Cls@1:0.820 Cls@5:0.969
Loc@1:0.734 Loc@5:0.883 Loc_gt:0.898

Val Epoch: [17][11/46] Loss 0.6407 (0.7731)
Cls@1:0.783 Cls@5:0.955
Loc@1:0.684 Loc@5:0.830 Loc_gt:0.866

Val Epoch: [17][21/46] Loss 0.6522 (0.7260)
Cls@1:0.801 Cls@5:0.953
Loc@1:0.712 Loc@5:0.844 Loc_gt:0.884

Val Epoch: [17][31/46] Loss 1.1568 (0.8259)
Cls@1:0.779 Cls@5:0.943
Loc@1:0.691 Loc@5:0.833 Loc_gt:0.878

Val Epoch: [17][41/46] Loss 0.9382 (0.8103)
Cls@1:0.785 Cls@5:0.944
Loc@1:0.689 Loc@5:0.828 Loc_gt:0.870

Val Epoch: [17][46/46] Loss 0.2736 (0.7843)
Cls@1:0.793 Cls@5:0.945
Loc@1:0.697 Loc@5:0.830 Loc_gt:0.871

wrong_details:4039 1198 0 419 136 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-34
Train Epoch: [18][1/47],lr: 0.00005 Loss 0.0635 (0.0635) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [18][11/47],lr: 0.00005 Loss 0.0894 (0.1066) Prec@1 100.000 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [18][21/47],lr: 0.00005 Loss 0.1175 (0.1038) Prec@1 98.438 (99.182) Prec@5 100.000 (99.963)
Train Epoch: [18][31/47],lr: 0.00005 Loss 0.1123 (0.1016) Prec@1 98.438 (98.942) Prec@5 100.000 (99.975)
Train Epoch: [18][41/47],lr: 0.00005 Loss 0.0851 (0.1038) Prec@1 100.000 (99.009) Prec@5 100.000 (99.962)
Train Epoch: [18][47/47],lr: 0.00005 Loss 0.0918 (0.1034) Prec@1 98.113 (99.049) Prec@5 100.000 (99.967)
Val Epoch: [18][1/46] Loss 0.6252 (0.6252)
Cls@1:0.836 Cls@5:0.969
Loc@1:0.766 Loc@5:0.891 Loc_gt:0.906

Val Epoch: [18][11/46] Loss 0.6177 (0.7739)
Cls@1:0.786 Cls@5:0.950
Loc@1:0.685 Loc@5:0.825 Loc_gt:0.865

Val Epoch: [18][21/46] Loss 0.5489 (0.7181)
Cls@1:0.810 Cls@5:0.952
Loc@1:0.722 Loc@5:0.844 Loc_gt:0.884

Val Epoch: [18][31/46] Loss 1.2410 (0.8263)
Cls@1:0.783 Cls@5:0.943
Loc@1:0.698 Loc@5:0.835 Loc_gt:0.880

Val Epoch: [18][41/46] Loss 0.9537 (0.8045)
Cls@1:0.789 Cls@5:0.946
Loc@1:0.699 Loc@5:0.835 Loc_gt:0.877

Val Epoch: [18][46/46] Loss 0.2785 (0.7766)
Cls@1:0.798 Cls@5:0.948
Loc@1:0.707 Loc@5:0.836 Loc_gt:0.877

wrong_details:4097 1172 0 389 134 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-36
Train Epoch: [19][1/47],lr: 0.00005 Loss 0.1170 (0.1170) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [19][11/47],lr: 0.00005 Loss 0.0662 (0.0769) Prec@1 100.000 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [19][21/47],lr: 0.00005 Loss 0.0650 (0.0773) Prec@1 99.219 (99.368) Prec@5 100.000 (100.000)
Train Epoch: [19][31/47],lr: 0.00005 Loss 0.0754 (0.0747) Prec@1 100.000 (99.446) Prec@5 100.000 (100.000)
Train Epoch: [19][41/47],lr: 0.00005 Loss 0.0607 (0.0735) Prec@1 99.219 (99.486) Prec@5 100.000 (100.000)
Train Epoch: [19][47/47],lr: 0.00005 Loss 0.0391 (0.0724) Prec@1 100.000 (99.516) Prec@5 100.000 (100.000)
Val Epoch: [19][1/46] Loss 0.6548 (0.6548)
Cls@1:0.820 Cls@5:0.961
Loc@1:0.758 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [19][11/46] Loss 0.5827 (0.7772)
Cls@1:0.786 Cls@5:0.951
Loc@1:0.685 Loc@5:0.823 Loc_gt:0.862

Val Epoch: [19][21/46] Loss 0.6767 (0.7287)
Cls@1:0.807 Cls@5:0.952
Loc@1:0.716 Loc@5:0.840 Loc_gt:0.880

Val Epoch: [19][31/46] Loss 1.1185 (0.8232)
Cls@1:0.788 Cls@5:0.941
Loc@1:0.697 Loc@5:0.827 Loc_gt:0.873

Val Epoch: [19][41/46] Loss 0.9338 (0.8153)
Cls@1:0.792 Cls@5:0.943
Loc@1:0.697 Loc@5:0.828 Loc_gt:0.870

Val Epoch: [19][46/46] Loss 0.3062 (0.7893)
Cls@1:0.799 Cls@5:0.945
Loc@1:0.705 Loc@5:0.830 Loc_gt:0.871

wrong_details:4083 1164 0 395 149 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-40
Train Epoch: [20][1/47],lr: 0.00005 Loss 0.0586 (0.0586) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [20][11/47],lr: 0.00005 Loss 0.0757 (0.0850) Prec@1 99.219 (99.077) Prec@5 100.000 (99.929)
Train Epoch: [20][21/47],lr: 0.00005 Loss 0.0621 (0.0808) Prec@1 100.000 (99.293) Prec@5 100.000 (99.963)
Train Epoch: [20][31/47],lr: 0.00005 Loss 0.1341 (0.0813) Prec@1 97.656 (99.143) Prec@5 100.000 (99.975)
Train Epoch: [20][41/47],lr: 0.00005 Loss 0.0869 (0.0794) Prec@1 100.000 (99.238) Prec@5 100.000 (99.981)
Train Epoch: [20][47/47],lr: 0.00005 Loss 0.0745 (0.0775) Prec@1 99.057 (99.266) Prec@5 100.000 (99.983)
Val Epoch: [20][1/46] Loss 0.6317 (0.6317)
Cls@1:0.836 Cls@5:0.961
Loc@1:0.766 Loc@5:0.891 Loc_gt:0.930

Val Epoch: [20][11/46] Loss 0.6124 (0.8026)
Cls@1:0.784 Cls@5:0.955
Loc@1:0.684 Loc@5:0.828 Loc_gt:0.868

Val Epoch: [20][21/46] Loss 0.5949 (0.7360)
Cls@1:0.807 Cls@5:0.955
Loc@1:0.714 Loc@5:0.842 Loc_gt:0.881

Val Epoch: [20][31/46] Loss 1.1237 (0.8315)
Cls@1:0.784 Cls@5:0.945
Loc@1:0.694 Loc@5:0.833 Loc_gt:0.877

Val Epoch: [20][41/46] Loss 0.9430 (0.8212)
Cls@1:0.788 Cls@5:0.945
Loc@1:0.696 Loc@5:0.832 Loc_gt:0.874

Val Epoch: [20][46/46] Loss 0.1878 (0.7933)
Cls@1:0.796 Cls@5:0.947
Loc@1:0.703 Loc@5:0.834 Loc_gt:0.873

wrong_details:4075 1182 0 386 147 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-44
Train Epoch: [21][1/47],lr: 0.00005 Loss 0.0527 (0.0527) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [21][11/47],lr: 0.00005 Loss 0.0721 (0.0673) Prec@1 98.438 (99.290) Prec@5 100.000 (99.929)
Train Epoch: [21][21/47],lr: 0.00005 Loss 0.0620 (0.0641) Prec@1 100.000 (99.368) Prec@5 100.000 (99.963)
Train Epoch: [21][31/47],lr: 0.00005 Loss 0.0845 (0.0666) Prec@1 99.219 (99.370) Prec@5 100.000 (99.975)
Train Epoch: [21][41/47],lr: 0.00005 Loss 0.0336 (0.0633) Prec@1 100.000 (99.447) Prec@5 100.000 (99.981)
Train Epoch: [21][47/47],lr: 0.00005 Loss 0.1105 (0.0652) Prec@1 100.000 (99.399) Prec@5 100.000 (99.983)
Val Epoch: [21][1/46] Loss 0.6695 (0.6695)
Cls@1:0.797 Cls@5:0.969
Loc@1:0.727 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [21][11/46] Loss 0.6130 (0.8032)
Cls@1:0.777 Cls@5:0.951
Loc@1:0.673 Loc@5:0.825 Loc_gt:0.866

Val Epoch: [21][21/46] Loss 0.5890 (0.7451)
Cls@1:0.807 Cls@5:0.950
Loc@1:0.716 Loc@5:0.842 Loc_gt:0.886

Val Epoch: [21][31/46] Loss 1.2195 (0.8393)
Cls@1:0.784 Cls@5:0.941
Loc@1:0.696 Loc@5:0.833 Loc_gt:0.880

Val Epoch: [21][41/46] Loss 1.0710 (0.8256)
Cls@1:0.789 Cls@5:0.943
Loc@1:0.696 Loc@5:0.832 Loc_gt:0.876

Val Epoch: [21][46/46] Loss 0.2066 (0.7986)
Cls@1:0.795 Cls@5:0.945
Loc@1:0.702 Loc@5:0.833 Loc_gt:0.876

wrong_details:4070 1185 0 400 137 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-48
Train Epoch: [22][1/47],lr: 0.00005 Loss 0.0875 (0.0875) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [22][11/47],lr: 0.00005 Loss 0.1110 (0.0683) Prec@1 97.656 (99.077) Prec@5 100.000 (100.000)
Train Epoch: [22][21/47],lr: 0.00005 Loss 0.1261 (0.0694) Prec@1 99.219 (98.996) Prec@5 100.000 (100.000)
Train Epoch: [22][31/47],lr: 0.00005 Loss 0.0453 (0.0651) Prec@1 100.000 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [22][41/47],lr: 0.00005 Loss 0.0382 (0.0666) Prec@1 100.000 (99.314) Prec@5 100.000 (100.000)
Train Epoch: [22][47/47],lr: 0.00005 Loss 0.0961 (0.0654) Prec@1 99.057 (99.349) Prec@5 99.057 (99.983)
Val Epoch: [22][1/46] Loss 0.6254 (0.6254)
Cls@1:0.844 Cls@5:0.977
Loc@1:0.773 Loc@5:0.898 Loc_gt:0.914

Val Epoch: [22][11/46] Loss 0.6711 (0.8193)
Cls@1:0.786 Cls@5:0.948
Loc@1:0.681 Loc@5:0.819 Loc_gt:0.863

Val Epoch: [22][21/46] Loss 0.6088 (0.7570)
Cls@1:0.806 Cls@5:0.951
Loc@1:0.712 Loc@5:0.836 Loc_gt:0.879

Val Epoch: [22][31/46] Loss 1.2085 (0.8615)
Cls@1:0.781 Cls@5:0.940
Loc@1:0.689 Loc@5:0.825 Loc_gt:0.872

Val Epoch: [22][41/46] Loss 0.9681 (0.8505)
Cls@1:0.784 Cls@5:0.942
Loc@1:0.688 Loc@5:0.824 Loc_gt:0.867

Val Epoch: [22][46/46] Loss 0.2516 (0.8196)
Cls@1:0.793 Cls@5:0.945
Loc@1:0.696 Loc@5:0.826 Loc_gt:0.868

wrong_details:4035 1201 0 425 130 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-50
Train Epoch: [23][1/47],lr: 0.00005 Loss 0.0289 (0.0289) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [23][11/47],lr: 0.00005 Loss 0.0372 (0.0573) Prec@1 99.219 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [23][21/47],lr: 0.00005 Loss 0.0627 (0.0605) Prec@1 100.000 (99.405) Prec@5 100.000 (100.000)
Train Epoch: [23][31/47],lr: 0.00005 Loss 0.0527 (0.0606) Prec@1 100.000 (99.370) Prec@5 100.000 (100.000)
Train Epoch: [23][41/47],lr: 0.00005 Loss 0.0414 (0.0598) Prec@1 100.000 (99.371) Prec@5 100.000 (100.000)
Train Epoch: [23][47/47],lr: 0.00005 Loss 0.0353 (0.0581) Prec@1 100.000 (99.433) Prec@5 100.000 (100.000)
Val Epoch: [23][1/46] Loss 0.5897 (0.5897)
Cls@1:0.844 Cls@5:0.961
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [23][11/46] Loss 0.6251 (0.8162)
Cls@1:0.783 Cls@5:0.951
Loc@1:0.685 Loc@5:0.827 Loc_gt:0.867

Val Epoch: [23][21/46] Loss 0.6038 (0.7549)
Cls@1:0.808 Cls@5:0.951
Loc@1:0.720 Loc@5:0.842 Loc_gt:0.884

Val Epoch: [23][31/46] Loss 1.2160 (0.8607)
Cls@1:0.783 Cls@5:0.940
Loc@1:0.693 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [23][41/46] Loss 1.0475 (0.8514)
Cls@1:0.785 Cls@5:0.942
Loc@1:0.691 Loc@5:0.827 Loc_gt:0.871

Val Epoch: [23][46/46] Loss 0.1622 (0.8180)
Cls@1:0.793 Cls@5:0.945
Loc@1:0.698 Loc@5:0.829 Loc_gt:0.871

wrong_details:4047 1198 0 406 139 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-54
Train Epoch: [24][1/47],lr: 0.00005 Loss 0.0394 (0.0394) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [24][11/47],lr: 0.00005 Loss 0.0349 (0.0609) Prec@1 100.000 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [24][21/47],lr: 0.00005 Loss 0.0162 (0.0551) Prec@1 100.000 (99.405) Prec@5 100.000 (99.963)
Train Epoch: [24][31/47],lr: 0.00005 Loss 0.0697 (0.0499) Prec@1 99.219 (99.521) Prec@5 100.000 (99.975)
Train Epoch: [24][41/47],lr: 0.00005 Loss 0.0260 (0.0501) Prec@1 100.000 (99.524) Prec@5 100.000 (99.981)
Train Epoch: [24][47/47],lr: 0.00005 Loss 0.0587 (0.0490) Prec@1 100.000 (99.550) Prec@5 100.000 (99.983)
Val Epoch: [24][1/46] Loss 0.6636 (0.6636)
Cls@1:0.828 Cls@5:0.961
Loc@1:0.758 Loc@5:0.891 Loc_gt:0.914

Val Epoch: [24][11/46] Loss 0.7147 (0.8249)
Cls@1:0.778 Cls@5:0.952
Loc@1:0.678 Loc@5:0.828 Loc_gt:0.866

Val Epoch: [24][21/46] Loss 0.5788 (0.7585)
Cls@1:0.802 Cls@5:0.953
Loc@1:0.713 Loc@5:0.844 Loc_gt:0.883

Val Epoch: [24][31/46] Loss 1.3588 (0.8776)
Cls@1:0.777 Cls@5:0.939
Loc@1:0.690 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [24][41/46] Loss 1.0404 (0.8587)
Cls@1:0.782 Cls@5:0.942
Loc@1:0.691 Loc@5:0.828 Loc_gt:0.872

Val Epoch: [24][46/46] Loss 0.1799 (0.8243)
Cls@1:0.792 Cls@5:0.945
Loc@1:0.700 Loc@5:0.831 Loc_gt:0.872

wrong_details:4058 1207 0 380 146 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-19-59
Train Epoch: [25][1/47],lr: 0.00005 Loss 0.0267 (0.0267) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [25][11/47],lr: 0.00005 Loss 0.0618 (0.0501) Prec@1 99.219 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [25][21/47],lr: 0.00005 Loss 0.0517 (0.0454) Prec@1 99.219 (99.665) Prec@5 100.000 (100.000)
Train Epoch: [25][31/47],lr: 0.00005 Loss 0.0370 (0.0463) Prec@1 100.000 (99.672) Prec@5 100.000 (100.000)
Train Epoch: [25][41/47],lr: 0.00005 Loss 0.0384 (0.0465) Prec@1 100.000 (99.581) Prec@5 100.000 (100.000)
Train Epoch: [25][47/47],lr: 0.00005 Loss 0.0488 (0.0464) Prec@1 100.000 (99.616) Prec@5 100.000 (100.000)
Val Epoch: [25][1/46] Loss 0.6319 (0.6319)
Cls@1:0.844 Cls@5:0.953
Loc@1:0.797 Loc@5:0.906 Loc_gt:0.945

Val Epoch: [25][11/46] Loss 0.5901 (0.8155)
Cls@1:0.783 Cls@5:0.950
Loc@1:0.681 Loc@5:0.825 Loc_gt:0.864

Val Epoch: [25][21/46] Loss 0.6068 (0.7617)
Cls@1:0.805 Cls@5:0.951
Loc@1:0.715 Loc@5:0.842 Loc_gt:0.882

Val Epoch: [25][31/46] Loss 1.1654 (0.8653)
Cls@1:0.781 Cls@5:0.941
Loc@1:0.690 Loc@5:0.829 Loc_gt:0.874

Val Epoch: [25][41/46] Loss 1.2914 (0.8571)
Cls@1:0.782 Cls@5:0.943
Loc@1:0.688 Loc@5:0.829 Loc_gt:0.871

Val Epoch: [25][46/46] Loss 0.1324 (0.8259)
Cls@1:0.790 Cls@5:0.945
Loc@1:0.696 Loc@5:0.830 Loc_gt:0.870

wrong_details:4030 1217 0 410 135 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-01
Train Epoch: [26][1/47],lr: 0.00005 Loss 0.0231 (0.0231) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [26][11/47],lr: 0.00005 Loss 0.0597 (0.0416) Prec@1 100.000 (99.503) Prec@5 100.000 (100.000)
Train Epoch: [26][21/47],lr: 0.00005 Loss 0.0741 (0.0458) Prec@1 97.656 (99.405) Prec@5 100.000 (100.000)
Train Epoch: [26][31/47],lr: 0.00005 Loss 0.0571 (0.0471) Prec@1 100.000 (99.521) Prec@5 100.000 (100.000)
Train Epoch: [26][41/47],lr: 0.00005 Loss 0.0307 (0.0449) Prec@1 100.000 (99.505) Prec@5 100.000 (100.000)
Train Epoch: [26][47/47],lr: 0.00005 Loss 0.0279 (0.0447) Prec@1 100.000 (99.550) Prec@5 100.000 (100.000)
Val Epoch: [26][1/46] Loss 0.6558 (0.6558)
Cls@1:0.828 Cls@5:0.961
Loc@1:0.750 Loc@5:0.875 Loc_gt:0.906

Val Epoch: [26][11/46] Loss 0.7349 (0.8160)
Cls@1:0.781 Cls@5:0.945
Loc@1:0.667 Loc@5:0.808 Loc_gt:0.854

Val Epoch: [26][21/46] Loss 0.6452 (0.7640)
Cls@1:0.802 Cls@5:0.947
Loc@1:0.702 Loc@5:0.828 Loc_gt:0.872

Val Epoch: [26][31/46] Loss 1.2026 (0.8653)
Cls@1:0.782 Cls@5:0.937
Loc@1:0.683 Loc@5:0.818 Loc_gt:0.867

Val Epoch: [26][41/46] Loss 1.2107 (0.8562)
Cls@1:0.785 Cls@5:0.939
Loc@1:0.684 Loc@5:0.817 Loc_gt:0.863

Val Epoch: [26][46/46] Loss 0.1438 (0.8279)
Cls@1:0.795 Cls@5:0.941
Loc@1:0.693 Loc@5:0.819 Loc_gt:0.863

wrong_details:4016 1190 0 436 149 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-06
Train Epoch: [27][1/47],lr: 0.00005 Loss 0.0278 (0.0278) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [27][11/47],lr: 0.00005 Loss 0.0592 (0.0426) Prec@1 100.000 (99.574) Prec@5 100.000 (100.000)
Train Epoch: [27][21/47],lr: 0.00005 Loss 0.0464 (0.0406) Prec@1 100.000 (99.665) Prec@5 100.000 (100.000)
Train Epoch: [27][31/47],lr: 0.00005 Loss 0.0297 (0.0417) Prec@1 100.000 (99.597) Prec@5 100.000 (100.000)
Train Epoch: [27][41/47],lr: 0.00005 Loss 0.0661 (0.0414) Prec@1 98.438 (99.562) Prec@5 100.000 (100.000)
Train Epoch: [27][47/47],lr: 0.00005 Loss 0.0285 (0.0417) Prec@1 100.000 (99.550) Prec@5 100.000 (100.000)
Val Epoch: [27][1/46] Loss 0.6611 (0.6611)
Cls@1:0.828 Cls@5:0.953
Loc@1:0.727 Loc@5:0.844 Loc_gt:0.883

Val Epoch: [27][11/46] Loss 0.5768 (0.8248)
Cls@1:0.780 Cls@5:0.948
Loc@1:0.658 Loc@5:0.805 Loc_gt:0.847

Val Epoch: [27][21/46] Loss 0.6309 (0.7758)
Cls@1:0.802 Cls@5:0.951
Loc@1:0.699 Loc@5:0.827 Loc_gt:0.868

Val Epoch: [27][31/46] Loss 1.2285 (0.8767)
Cls@1:0.780 Cls@5:0.941
Loc@1:0.679 Loc@5:0.818 Loc_gt:0.864

Val Epoch: [27][41/46] Loss 1.0357 (0.8605)
Cls@1:0.785 Cls@5:0.944
Loc@1:0.680 Loc@5:0.817 Loc_gt:0.860

Val Epoch: [27][46/46] Loss 0.1784 (0.8314)
Cls@1:0.794 Cls@5:0.946
Loc@1:0.689 Loc@5:0.819 Loc_gt:0.860

wrong_details:3992 1191 0 456 151 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-08
Train Epoch: [28][1/47],lr: 0.00005 Loss 0.0217 (0.0217) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [28][11/47],lr: 0.00005 Loss 0.0439 (0.0387) Prec@1 99.219 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [28][21/47],lr: 0.00005 Loss 0.0664 (0.0366) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [28][31/47],lr: 0.00005 Loss 0.0118 (0.0353) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [28][41/47],lr: 0.00005 Loss 0.0304 (0.0329) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [28][47/47],lr: 0.00005 Loss 0.0187 (0.0336) Prec@1 100.000 (99.800) Prec@5 100.000 (100.000)
Val Epoch: [28][1/46] Loss 0.6763 (0.6763)
Cls@1:0.859 Cls@5:0.953
Loc@1:0.789 Loc@5:0.883 Loc_gt:0.922

Val Epoch: [28][11/46] Loss 0.6067 (0.8369)
Cls@1:0.786 Cls@5:0.942
Loc@1:0.676 Loc@5:0.811 Loc_gt:0.859

Val Epoch: [28][21/46] Loss 0.6329 (0.7737)
Cls@1:0.805 Cls@5:0.946
Loc@1:0.708 Loc@5:0.830 Loc_gt:0.876

Val Epoch: [28][31/46] Loss 1.1330 (0.8673)
Cls@1:0.785 Cls@5:0.939
Loc@1:0.694 Loc@5:0.828 Loc_gt:0.877

Val Epoch: [28][41/46] Loss 1.0446 (0.8561)
Cls@1:0.790 Cls@5:0.941
Loc@1:0.696 Loc@5:0.828 Loc_gt:0.873

Val Epoch: [28][46/46] Loss 0.1536 (0.8258)
Cls@1:0.799 Cls@5:0.943
Loc@1:0.705 Loc@5:0.830 Loc_gt:0.873

wrong_details:4085 1167 0 378 160 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-13
Train Epoch: [29][1/47],lr: 0.00005 Loss 0.0449 (0.0449) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [29][11/47],lr: 0.00005 Loss 0.0230 (0.0475) Prec@1 100.000 (99.645) Prec@5 100.000 (99.929)
Train Epoch: [29][21/47],lr: 0.00005 Loss 0.0297 (0.0396) Prec@1 99.219 (99.740) Prec@5 100.000 (99.963)
Train Epoch: [29][31/47],lr: 0.00005 Loss 0.0298 (0.0391) Prec@1 100.000 (99.748) Prec@5 100.000 (99.975)
Train Epoch: [29][41/47],lr: 0.00005 Loss 0.0361 (0.0366) Prec@1 99.219 (99.771) Prec@5 100.000 (99.981)
Train Epoch: [29][47/47],lr: 0.00005 Loss 0.0234 (0.0357) Prec@1 100.000 (99.783) Prec@5 100.000 (99.983)
Val Epoch: [29][1/46] Loss 0.6302 (0.6302)
Cls@1:0.844 Cls@5:0.961
Loc@1:0.773 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [29][11/46] Loss 0.6144 (0.8096)
Cls@1:0.796 Cls@5:0.945
Loc@1:0.693 Loc@5:0.820 Loc_gt:0.865

Val Epoch: [29][21/46] Loss 0.7127 (0.7638)
Cls@1:0.809 Cls@5:0.947
Loc@1:0.718 Loc@5:0.836 Loc_gt:0.880

Val Epoch: [29][31/46] Loss 1.1108 (0.8678)
Cls@1:0.786 Cls@5:0.939
Loc@1:0.697 Loc@5:0.830 Loc_gt:0.878

Val Epoch: [29][41/46] Loss 1.0407 (0.8586)
Cls@1:0.790 Cls@5:0.941
Loc@1:0.694 Loc@5:0.826 Loc_gt:0.871

Val Epoch: [29][46/46] Loss 0.1726 (0.8281)
Cls@1:0.799 Cls@5:0.943
Loc@1:0.702 Loc@5:0.828 Loc_gt:0.871

wrong_details:4066 1165 0 409 149 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-17
Train Epoch: [30][1/47],lr: 0.00001 Loss 0.0478 (0.0478) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [30][11/47],lr: 0.00001 Loss 0.0400 (0.0367) Prec@1 100.000 (99.503) Prec@5 100.000 (100.000)
Train Epoch: [30][21/47],lr: 0.00001 Loss 0.0308 (0.0377) Prec@1 100.000 (99.665) Prec@5 100.000 (99.963)
Train Epoch: [30][31/47],lr: 0.00001 Loss 0.0380 (0.0368) Prec@1 99.219 (99.622) Prec@5 100.000 (99.975)
Train Epoch: [30][41/47],lr: 0.00001 Loss 0.0309 (0.0364) Prec@1 100.000 (99.638) Prec@5 100.000 (99.981)
Train Epoch: [30][47/47],lr: 0.00001 Loss 0.0296 (0.0365) Prec@1 100.000 (99.650) Prec@5 100.000 (99.967)
Val Epoch: [30][1/46] Loss 0.6287 (0.6287)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [30][11/46] Loss 0.6163 (0.8035)
Cls@1:0.802 Cls@5:0.950
Loc@1:0.697 Loc@5:0.823 Loc_gt:0.864

Val Epoch: [30][21/46] Loss 0.6877 (0.7559)
Cls@1:0.813 Cls@5:0.950
Loc@1:0.721 Loc@5:0.839 Loc_gt:0.880

Val Epoch: [30][31/46] Loss 1.1360 (0.8600)
Cls@1:0.791 Cls@5:0.940
Loc@1:0.702 Loc@5:0.832 Loc_gt:0.879

Val Epoch: [30][41/46] Loss 1.0566 (0.8510)
Cls@1:0.794 Cls@5:0.942
Loc@1:0.698 Loc@5:0.828 Loc_gt:0.872

Val Epoch: [30][46/46] Loss 0.1623 (0.8210)
Cls@1:0.803 Cls@5:0.944
Loc@1:0.706 Loc@5:0.830 Loc_gt:0.872

wrong_details:4092 1144 0 400 153 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-20
Train Epoch: [31][1/47],lr: 0.00001 Loss 0.0356 (0.0356) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [31][11/47],lr: 0.00001 Loss 0.0207 (0.0323) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [31][21/47],lr: 0.00001 Loss 0.0544 (0.0323) Prec@1 98.438 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [31][31/47],lr: 0.00001 Loss 0.0135 (0.0315) Prec@1 100.000 (99.748) Prec@5 100.000 (100.000)
Train Epoch: [31][41/47],lr: 0.00001 Loss 0.0482 (0.0323) Prec@1 99.219 (99.695) Prec@5 100.000 (100.000)
Train Epoch: [31][47/47],lr: 0.00001 Loss 0.0102 (0.0327) Prec@1 100.000 (99.683) Prec@5 100.000 (100.000)
Val Epoch: [31][1/46] Loss 0.6189 (0.6189)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [31][11/46] Loss 0.6285 (0.8063)
Cls@1:0.800 Cls@5:0.949
Loc@1:0.691 Loc@5:0.819 Loc_gt:0.859

Val Epoch: [31][21/46] Loss 0.6947 (0.7599)
Cls@1:0.814 Cls@5:0.949
Loc@1:0.718 Loc@5:0.834 Loc_gt:0.876

Val Epoch: [31][31/46] Loss 1.1273 (0.8602)
Cls@1:0.794 Cls@5:0.939
Loc@1:0.700 Loc@5:0.826 Loc_gt:0.873

Val Epoch: [31][41/46] Loss 1.0255 (0.8500)
Cls@1:0.796 Cls@5:0.941
Loc@1:0.696 Loc@5:0.823 Loc_gt:0.866

Val Epoch: [31][46/46] Loss 0.1735 (0.8200)
Cls@1:0.804 Cls@5:0.944
Loc@1:0.705 Loc@5:0.825 Loc_gt:0.867

wrong_details:4082 1135 0 418 154 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-25
Train Epoch: [32][1/47],lr: 0.00001 Loss 0.0303 (0.0303) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [32][11/47],lr: 0.00001 Loss 0.0267 (0.0329) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [32][21/47],lr: 0.00001 Loss 0.0544 (0.0353) Prec@1 100.000 (99.777) Prec@5 100.000 (99.963)
Train Epoch: [32][31/47],lr: 0.00001 Loss 0.0196 (0.0329) Prec@1 100.000 (99.849) Prec@5 100.000 (99.975)
Train Epoch: [32][41/47],lr: 0.00001 Loss 0.0282 (0.0326) Prec@1 99.219 (99.809) Prec@5 100.000 (99.981)
Train Epoch: [32][47/47],lr: 0.00001 Loss 0.0174 (0.0320) Prec@1 100.000 (99.816) Prec@5 100.000 (99.983)
Val Epoch: [32][1/46] Loss 0.6135 (0.6135)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [32][11/46] Loss 0.6141 (0.8035)
Cls@1:0.795 Cls@5:0.949
Loc@1:0.685 Loc@5:0.817 Loc_gt:0.858

Val Epoch: [32][21/46] Loss 0.6929 (0.7607)
Cls@1:0.811 Cls@5:0.949
Loc@1:0.715 Loc@5:0.834 Loc_gt:0.876

Val Epoch: [32][31/46] Loss 1.1463 (0.8618)
Cls@1:0.790 Cls@5:0.939
Loc@1:0.697 Loc@5:0.826 Loc_gt:0.873

Val Epoch: [32][41/46] Loss 0.9936 (0.8519)
Cls@1:0.794 Cls@5:0.942
Loc@1:0.693 Loc@5:0.821 Loc_gt:0.865

Val Epoch: [32][46/46] Loss 0.1696 (0.8213)
Cls@1:0.803 Cls@5:0.944
Loc@1:0.702 Loc@5:0.824 Loc_gt:0.866

wrong_details:4067 1142 0 431 149 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-26
Train Epoch: [33][1/47],lr: 0.00001 Loss 0.0145 (0.0145) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [33][11/47],lr: 0.00001 Loss 0.0188 (0.0352) Prec@1 100.000 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [33][21/47],lr: 0.00001 Loss 0.0371 (0.0355) Prec@1 100.000 (99.628) Prec@5 100.000 (100.000)
Train Epoch: [33][31/47],lr: 0.00001 Loss 0.0193 (0.0339) Prec@1 100.000 (99.647) Prec@5 100.000 (100.000)
Train Epoch: [33][41/47],lr: 0.00001 Loss 0.0448 (0.0323) Prec@1 99.219 (99.676) Prec@5 100.000 (100.000)
Train Epoch: [33][47/47],lr: 0.00001 Loss 0.0207 (0.0308) Prec@1 100.000 (99.700) Prec@5 100.000 (100.000)
Val Epoch: [33][1/46] Loss 0.6077 (0.6077)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [33][11/46] Loss 0.6004 (0.8067)
Cls@1:0.795 Cls@5:0.947
Loc@1:0.685 Loc@5:0.813 Loc_gt:0.857

Val Epoch: [33][21/46] Loss 0.6739 (0.7599)
Cls@1:0.813 Cls@5:0.948
Loc@1:0.717 Loc@5:0.832 Loc_gt:0.876

Val Epoch: [33][31/46] Loss 1.1490 (0.8587)
Cls@1:0.794 Cls@5:0.939
Loc@1:0.701 Loc@5:0.826 Loc_gt:0.874

Val Epoch: [33][41/46] Loss 1.0271 (0.8496)
Cls@1:0.796 Cls@5:0.942
Loc@1:0.697 Loc@5:0.822 Loc_gt:0.866

Val Epoch: [33][46/46] Loss 0.1561 (0.8196)
Cls@1:0.804 Cls@5:0.944
Loc@1:0.706 Loc@5:0.825 Loc_gt:0.868

wrong_details:4088 1133 0 418 151 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-32
Train Epoch: [34][1/47],lr: 0.00001 Loss 0.0266 (0.0266) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [34][11/47],lr: 0.00001 Loss 0.0278 (0.0318) Prec@1 99.219 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [34][21/47],lr: 0.00001 Loss 0.0196 (0.0312) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [34][31/47],lr: 0.00001 Loss 0.0160 (0.0336) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [34][41/47],lr: 0.00001 Loss 0.0156 (0.0302) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [34][47/47],lr: 0.00001 Loss 0.0353 (0.0296) Prec@1 100.000 (99.850) Prec@5 100.000 (100.000)
Val Epoch: [34][1/46] Loss 0.6075 (0.6075)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [34][11/46] Loss 0.6114 (0.8146)
Cls@1:0.790 Cls@5:0.948
Loc@1:0.680 Loc@5:0.814 Loc_gt:0.857

Val Epoch: [34][21/46] Loss 0.6578 (0.7616)
Cls@1:0.812 Cls@5:0.948
Loc@1:0.716 Loc@5:0.834 Loc_gt:0.877

Val Epoch: [34][31/46] Loss 1.1554 (0.8573)
Cls@1:0.793 Cls@5:0.939
Loc@1:0.700 Loc@5:0.826 Loc_gt:0.874

Val Epoch: [34][41/46] Loss 1.0363 (0.8490)
Cls@1:0.795 Cls@5:0.941
Loc@1:0.696 Loc@5:0.823 Loc_gt:0.867

Val Epoch: [34][46/46] Loss 0.1515 (0.8189)
Cls@1:0.804 Cls@5:0.944
Loc@1:0.705 Loc@5:0.826 Loc_gt:0.868

wrong_details:4082 1138 0 428 142 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-34
Train Epoch: [35][1/47],lr: 0.00001 Loss 0.0193 (0.0193) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [35][11/47],lr: 0.00001 Loss 0.0113 (0.0294) Prec@1 100.000 (99.645) Prec@5 100.000 (99.929)
Train Epoch: [35][21/47],lr: 0.00001 Loss 0.0126 (0.0307) Prec@1 100.000 (99.740) Prec@5 100.000 (99.963)
Train Epoch: [35][31/47],lr: 0.00001 Loss 0.0131 (0.0301) Prec@1 100.000 (99.748) Prec@5 100.000 (99.975)
Train Epoch: [35][41/47],lr: 0.00001 Loss 0.0320 (0.0291) Prec@1 100.000 (99.809) Prec@5 100.000 (99.981)
Train Epoch: [35][47/47],lr: 0.00001 Loss 0.0267 (0.0294) Prec@1 100.000 (99.816) Prec@5 100.000 (99.983)
Val Epoch: [35][1/46] Loss 0.6197 (0.6197)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [35][11/46] Loss 0.6051 (0.8138)
Cls@1:0.791 Cls@5:0.949
Loc@1:0.681 Loc@5:0.815 Loc_gt:0.859

Val Epoch: [35][21/46] Loss 0.6507 (0.7595)
Cls@1:0.813 Cls@5:0.950
Loc@1:0.716 Loc@5:0.834 Loc_gt:0.876

Val Epoch: [35][31/46] Loss 1.1669 (0.8573)
Cls@1:0.794 Cls@5:0.940
Loc@1:0.700 Loc@5:0.826 Loc_gt:0.873

Val Epoch: [35][41/46] Loss 1.0432 (0.8484)
Cls@1:0.797 Cls@5:0.942
Loc@1:0.695 Loc@5:0.822 Loc_gt:0.865

Val Epoch: [35][46/46] Loss 0.1589 (0.8188)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.703 Loc@5:0.824 Loc_gt:0.866

wrong_details:4072 1133 0 446 139 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-38
Train Epoch: [36][1/47],lr: 0.00001 Loss 0.0245 (0.0245) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [36][11/47],lr: 0.00001 Loss 0.0130 (0.0268) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [36][21/47],lr: 0.00001 Loss 0.0332 (0.0277) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [36][31/47],lr: 0.00001 Loss 0.0561 (0.0273) Prec@1 99.219 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [36][41/47],lr: 0.00001 Loss 0.0271 (0.0272) Prec@1 100.000 (99.790) Prec@5 100.000 (99.981)
Train Epoch: [36][47/47],lr: 0.00001 Loss 0.0216 (0.0267) Prec@1 99.057 (99.783) Prec@5 100.000 (99.983)
Val Epoch: [36][1/46] Loss 0.6079 (0.6079)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [36][11/46] Loss 0.6170 (0.8187)
Cls@1:0.789 Cls@5:0.949
Loc@1:0.679 Loc@5:0.815 Loc_gt:0.857

Val Epoch: [36][21/46] Loss 0.6431 (0.7610)
Cls@1:0.812 Cls@5:0.950
Loc@1:0.716 Loc@5:0.834 Loc_gt:0.876

Val Epoch: [36][31/46] Loss 1.1597 (0.8576)
Cls@1:0.794 Cls@5:0.941
Loc@1:0.700 Loc@5:0.828 Loc_gt:0.873

Val Epoch: [36][41/46] Loss 1.0437 (0.8491)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.696 Loc@5:0.824 Loc_gt:0.866

Val Epoch: [36][46/46] Loss 0.1586 (0.8188)
Cls@1:0.805 Cls@5:0.945
Loc@1:0.705 Loc@5:0.826 Loc_gt:0.867

wrong_details:4085 1131 0 441 133 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-43
Train Epoch: [37][1/47],lr: 0.00001 Loss 0.0162 (0.0162) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [37][11/47],lr: 0.00001 Loss 0.0413 (0.0259) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [37][21/47],lr: 0.00001 Loss 0.0332 (0.0246) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [37][31/47],lr: 0.00001 Loss 0.0339 (0.0287) Prec@1 99.219 (99.798) Prec@5 100.000 (100.000)
Train Epoch: [37][41/47],lr: 0.00001 Loss 0.0229 (0.0287) Prec@1 99.219 (99.790) Prec@5 100.000 (100.000)
Train Epoch: [37][47/47],lr: 0.00001 Loss 0.0287 (0.0278) Prec@1 100.000 (99.816) Prec@5 100.000 (100.000)
Val Epoch: [37][1/46] Loss 0.6039 (0.6039)
Cls@1:0.844 Cls@5:0.969
Loc@1:0.773 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [37][11/46] Loss 0.6154 (0.8103)
Cls@1:0.788 Cls@5:0.950
Loc@1:0.680 Loc@5:0.818 Loc_gt:0.859

Val Epoch: [37][21/46] Loss 0.6537 (0.7591)
Cls@1:0.808 Cls@5:0.949
Loc@1:0.713 Loc@5:0.834 Loc_gt:0.876

Val Epoch: [37][31/46] Loss 1.1797 (0.8586)
Cls@1:0.790 Cls@5:0.940
Loc@1:0.697 Loc@5:0.827 Loc_gt:0.873

Val Epoch: [37][41/46] Loss 1.0247 (0.8500)
Cls@1:0.795 Cls@5:0.942
Loc@1:0.695 Loc@5:0.823 Loc_gt:0.865

Val Epoch: [37][46/46] Loss 0.1425 (0.8195)
Cls@1:0.803 Cls@5:0.945
Loc@1:0.703 Loc@5:0.826 Loc_gt:0.866

wrong_details:4075 1139 0 445 132 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-46
Train Epoch: [38][1/47],lr: 0.00001 Loss 0.0136 (0.0136) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [38][11/47],lr: 0.00001 Loss 0.0622 (0.0345) Prec@1 99.219 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [38][21/47],lr: 0.00001 Loss 0.0156 (0.0294) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [38][31/47],lr: 0.00001 Loss 0.0199 (0.0287) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [38][41/47],lr: 0.00001 Loss 0.0329 (0.0297) Prec@1 100.000 (99.752) Prec@5 100.000 (99.981)
Train Epoch: [38][47/47],lr: 0.00001 Loss 0.0453 (0.0298) Prec@1 99.057 (99.716) Prec@5 100.000 (99.983)
Val Epoch: [38][1/46] Loss 0.6033 (0.6033)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.922

Val Epoch: [38][11/46] Loss 0.6146 (0.8187)
Cls@1:0.786 Cls@5:0.949
Loc@1:0.678 Loc@5:0.817 Loc_gt:0.859

Val Epoch: [38][21/46] Loss 0.6396 (0.7646)
Cls@1:0.809 Cls@5:0.949
Loc@1:0.713 Loc@5:0.835 Loc_gt:0.877

Val Epoch: [38][31/46] Loss 1.1757 (0.8614)
Cls@1:0.791 Cls@5:0.940
Loc@1:0.698 Loc@5:0.828 Loc_gt:0.875

Val Epoch: [38][41/46] Loss 1.0429 (0.8502)
Cls@1:0.796 Cls@5:0.942
Loc@1:0.696 Loc@5:0.824 Loc_gt:0.867

Val Epoch: [38][46/46] Loss 0.1522 (0.8201)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.704 Loc@5:0.826 Loc_gt:0.868

wrong_details:4078 1138 0 441 133 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-51
Train Epoch: [39][1/47],lr: 0.00001 Loss 0.0175 (0.0175) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [39][11/47],lr: 0.00001 Loss 0.0088 (0.0273) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [39][21/47],lr: 0.00001 Loss 0.1012 (0.0351) Prec@1 100.000 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [39][31/47],lr: 0.00001 Loss 0.0884 (0.0320) Prec@1 98.438 (99.748) Prec@5 100.000 (100.000)
Train Epoch: [39][41/47],lr: 0.00001 Loss 0.0288 (0.0333) Prec@1 99.219 (99.733) Prec@5 100.000 (99.962)
Train Epoch: [39][47/47],lr: 0.00001 Loss 0.0596 (0.0321) Prec@1 100.000 (99.766) Prec@5 100.000 (99.967)
Val Epoch: [39][1/46] Loss 0.6048 (0.6048)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [39][11/46] Loss 0.6095 (0.8187)
Cls@1:0.788 Cls@5:0.951
Loc@1:0.678 Loc@5:0.818 Loc_gt:0.859

Val Epoch: [39][21/46] Loss 0.6288 (0.7646)
Cls@1:0.810 Cls@5:0.950
Loc@1:0.714 Loc@5:0.836 Loc_gt:0.878

Val Epoch: [39][31/46] Loss 1.1731 (0.8616)
Cls@1:0.793 Cls@5:0.940
Loc@1:0.699 Loc@5:0.828 Loc_gt:0.875

Val Epoch: [39][41/46] Loss 1.0636 (0.8507)
Cls@1:0.796 Cls@5:0.942
Loc@1:0.697 Loc@5:0.825 Loc_gt:0.868

Val Epoch: [39][46/46] Loss 0.1648 (0.8202)
Cls@1:0.805 Cls@5:0.945
Loc@1:0.705 Loc@5:0.827 Loc_gt:0.868

wrong_details:4086 1128 0 440 136 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-52
Train Epoch: [40][1/47],lr: 0.00001 Loss 0.0203 (0.0203) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [40][11/47],lr: 0.00001 Loss 0.0192 (0.0315) Prec@1 99.219 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [40][21/47],lr: 0.00001 Loss 0.0155 (0.0294) Prec@1 100.000 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [40][31/47],lr: 0.00001 Loss 0.0211 (0.0265) Prec@1 100.000 (99.849) Prec@5 100.000 (100.000)
Train Epoch: [40][41/47],lr: 0.00001 Loss 0.0168 (0.0248) Prec@1 100.000 (99.886) Prec@5 100.000 (100.000)
Train Epoch: [40][47/47],lr: 0.00001 Loss 0.0165 (0.0235) Prec@1 100.000 (99.900) Prec@5 100.000 (100.000)
Val Epoch: [40][1/46] Loss 0.6049 (0.6049)
Cls@1:0.859 Cls@5:0.969
Loc@1:0.797 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [40][11/46] Loss 0.6059 (0.8173)
Cls@1:0.791 Cls@5:0.947
Loc@1:0.682 Loc@5:0.817 Loc_gt:0.862

Val Epoch: [40][21/46] Loss 0.6305 (0.7625)
Cls@1:0.813 Cls@5:0.949
Loc@1:0.718 Loc@5:0.836 Loc_gt:0.879

Val Epoch: [40][31/46] Loss 1.1475 (0.8605)
Cls@1:0.794 Cls@5:0.939
Loc@1:0.702 Loc@5:0.828 Loc_gt:0.876

Val Epoch: [40][41/46] Loss 1.0611 (0.8506)
Cls@1:0.797 Cls@5:0.942
Loc@1:0.699 Loc@5:0.826 Loc_gt:0.869

Val Epoch: [40][46/46] Loss 0.1577 (0.8198)
Cls@1:0.806 Cls@5:0.944
Loc@1:0.707 Loc@5:0.828 Loc_gt:0.870

wrong_details:4099 1125 0 430 137 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-20-57
Train Epoch: [41][1/47],lr: 0.00001 Loss 0.0188 (0.0188) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [41][11/47],lr: 0.00001 Loss 0.0134 (0.0223) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [41][21/47],lr: 0.00001 Loss 0.0155 (0.0273) Prec@1 100.000 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [41][31/47],lr: 0.00001 Loss 0.0255 (0.0266) Prec@1 100.000 (99.798) Prec@5 100.000 (100.000)
Train Epoch: [41][41/47],lr: 0.00001 Loss 0.0451 (0.0255) Prec@1 99.219 (99.790) Prec@5 100.000 (100.000)
Train Epoch: [41][47/47],lr: 0.00001 Loss 0.0582 (0.0249) Prec@1 99.057 (99.800) Prec@5 100.000 (100.000)
Val Epoch: [41][1/46] Loss 0.6143 (0.6143)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [41][11/46] Loss 0.6042 (0.8150)
Cls@1:0.788 Cls@5:0.951
Loc@1:0.679 Loc@5:0.817 Loc_gt:0.859

Val Epoch: [41][21/46] Loss 0.6389 (0.7611)
Cls@1:0.812 Cls@5:0.950
Loc@1:0.716 Loc@5:0.834 Loc_gt:0.876

Val Epoch: [41][31/46] Loss 1.1559 (0.8584)
Cls@1:0.792 Cls@5:0.940
Loc@1:0.699 Loc@5:0.827 Loc_gt:0.874

Val Epoch: [41][41/46] Loss 1.0731 (0.8480)
Cls@1:0.796 Cls@5:0.942
Loc@1:0.696 Loc@5:0.823 Loc_gt:0.867

Val Epoch: [41][46/46] Loss 0.1618 (0.8175)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.705 Loc@5:0.826 Loc_gt:0.868

wrong_details:4082 1134 0 440 135 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-00
Train Epoch: [42][1/47],lr: 0.00001 Loss 0.0106 (0.0106) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [42][11/47],lr: 0.00001 Loss 0.0180 (0.0283) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [42][21/47],lr: 0.00001 Loss 0.0071 (0.0244) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [42][31/47],lr: 0.00001 Loss 0.0066 (0.0257) Prec@1 100.000 (99.824) Prec@5 100.000 (100.000)
Train Epoch: [42][41/47],lr: 0.00001 Loss 0.0260 (0.0244) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [42][47/47],lr: 0.00001 Loss 0.0153 (0.0236) Prec@1 100.000 (99.850) Prec@5 100.000 (100.000)
Val Epoch: [42][1/46] Loss 0.6056 (0.6056)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [42][11/46] Loss 0.5866 (0.8164)
Cls@1:0.790 Cls@5:0.950
Loc@1:0.678 Loc@5:0.812 Loc_gt:0.854

Val Epoch: [42][21/46] Loss 0.6455 (0.7626)
Cls@1:0.812 Cls@5:0.950
Loc@1:0.714 Loc@5:0.832 Loc_gt:0.873

Val Epoch: [42][31/46] Loss 1.1589 (0.8600)
Cls@1:0.792 Cls@5:0.940
Loc@1:0.697 Loc@5:0.824 Loc_gt:0.871

Val Epoch: [42][41/46] Loss 1.0539 (0.8488)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.693 Loc@5:0.821 Loc_gt:0.864

Val Epoch: [42][46/46] Loss 0.1585 (0.8182)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.702 Loc@5:0.823 Loc_gt:0.865

wrong_details:4065 1137 0 454 136 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-03
Train Epoch: [43][1/47],lr: 0.00001 Loss 0.0188 (0.0188) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [43][11/47],lr: 0.00001 Loss 0.0167 (0.0222) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [43][21/47],lr: 0.00001 Loss 0.0156 (0.0246) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [43][31/47],lr: 0.00001 Loss 0.0100 (0.0248) Prec@1 100.000 (99.924) Prec@5 100.000 (100.000)
Train Epoch: [43][41/47],lr: 0.00001 Loss 0.0457 (0.0249) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Train Epoch: [43][47/47],lr: 0.00001 Loss 0.0314 (0.0252) Prec@1 99.057 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [43][1/46] Loss 0.6007 (0.6007)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [43][11/46] Loss 0.5928 (0.8253)
Cls@1:0.787 Cls@5:0.948
Loc@1:0.675 Loc@5:0.815 Loc_gt:0.857

Val Epoch: [43][21/46] Loss 0.6318 (0.7677)
Cls@1:0.809 Cls@5:0.949
Loc@1:0.710 Loc@5:0.831 Loc_gt:0.874

Val Epoch: [43][31/46] Loss 1.1379 (0.8603)
Cls@1:0.791 Cls@5:0.940
Loc@1:0.695 Loc@5:0.824 Loc_gt:0.871

Val Epoch: [43][41/46] Loss 1.0594 (0.8494)
Cls@1:0.794 Cls@5:0.942
Loc@1:0.692 Loc@5:0.821 Loc_gt:0.864

Val Epoch: [43][46/46] Loss 0.1547 (0.8186)
Cls@1:0.803 Cls@5:0.945
Loc@1:0.700 Loc@5:0.824 Loc_gt:0.865

wrong_details:4057 1142 0 460 133 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-09
Train Epoch: [44][1/47],lr: 0.00001 Loss 0.0305 (0.0305) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [44][11/47],lr: 0.00001 Loss 0.0142 (0.0322) Prec@1 100.000 (99.645) Prec@5 100.000 (100.000)
Train Epoch: [44][21/47],lr: 0.00001 Loss 0.0332 (0.0303) Prec@1 98.438 (99.628) Prec@5 100.000 (100.000)
Train Epoch: [44][31/47],lr: 0.00001 Loss 0.0260 (0.0293) Prec@1 100.000 (99.723) Prec@5 100.000 (100.000)
Train Epoch: [44][41/47],lr: 0.00001 Loss 0.0300 (0.0309) Prec@1 99.219 (99.676) Prec@5 100.000 (100.000)
Train Epoch: [44][47/47],lr: 0.00001 Loss 0.0161 (0.0307) Prec@1 100.000 (99.700) Prec@5 100.000 (99.983)
Val Epoch: [44][1/46] Loss 0.5885 (0.5885)
Cls@1:0.859 Cls@5:0.969
Loc@1:0.789 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [44][11/46] Loss 0.5990 (0.8211)
Cls@1:0.788 Cls@5:0.949
Loc@1:0.680 Loc@5:0.817 Loc_gt:0.859

Val Epoch: [44][21/46] Loss 0.6558 (0.7706)
Cls@1:0.806 Cls@5:0.949
Loc@1:0.711 Loc@5:0.833 Loc_gt:0.875

Val Epoch: [44][31/46] Loss 1.1545 (0.8668)
Cls@1:0.788 Cls@5:0.941
Loc@1:0.694 Loc@5:0.825 Loc_gt:0.872

Val Epoch: [44][41/46] Loss 1.0339 (0.8549)
Cls@1:0.792 Cls@5:0.943
Loc@1:0.692 Loc@5:0.822 Loc_gt:0.865

Val Epoch: [44][46/46] Loss 0.1519 (0.8239)
Cls@1:0.801 Cls@5:0.945
Loc@1:0.700 Loc@5:0.825 Loc_gt:0.866

wrong_details:4055 1155 0 448 134 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-10
Train Epoch: [45][1/47],lr: 0.00001 Loss 0.0299 (0.0299) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [45][11/47],lr: 0.00001 Loss 0.0225 (0.0252) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [45][21/47],lr: 0.00001 Loss 0.0160 (0.0258) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [45][31/47],lr: 0.00001 Loss 0.0478 (0.0272) Prec@1 100.000 (99.798) Prec@5 100.000 (100.000)
Train Epoch: [45][41/47],lr: 0.00001 Loss 0.0699 (0.0254) Prec@1 98.438 (99.790) Prec@5 99.219 (99.981)
Train Epoch: [45][47/47],lr: 0.00001 Loss 0.0084 (0.0258) Prec@1 100.000 (99.800) Prec@5 100.000 (99.983)
Val Epoch: [45][1/46] Loss 0.5922 (0.5922)
Cls@1:0.859 Cls@5:0.969
Loc@1:0.781 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [45][11/46] Loss 0.5953 (0.8240)
Cls@1:0.786 Cls@5:0.952
Loc@1:0.677 Loc@5:0.820 Loc_gt:0.859

Val Epoch: [45][21/46] Loss 0.6307 (0.7680)
Cls@1:0.807 Cls@5:0.951
Loc@1:0.712 Loc@5:0.835 Loc_gt:0.876

Val Epoch: [45][31/46] Loss 1.1957 (0.8639)
Cls@1:0.789 Cls@5:0.942
Loc@1:0.695 Loc@5:0.827 Loc_gt:0.874

Val Epoch: [45][41/46] Loss 1.0720 (0.8520)
Cls@1:0.793 Cls@5:0.944
Loc@1:0.692 Loc@5:0.824 Loc_gt:0.868

Val Epoch: [45][46/46] Loss 0.1605 (0.8213)
Cls@1:0.802 Cls@5:0.946
Loc@1:0.701 Loc@5:0.826 Loc_gt:0.868

wrong_details:4062 1146 0 456 128 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-15
Train Epoch: [46][1/47],lr: 0.00001 Loss 0.0228 (0.0228) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [46][11/47],lr: 0.00001 Loss 0.0225 (0.0215) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [46][21/47],lr: 0.00001 Loss 0.0224 (0.0261) Prec@1 100.000 (99.777) Prec@5 100.000 (99.963)
Train Epoch: [46][31/47],lr: 0.00001 Loss 0.0143 (0.0251) Prec@1 100.000 (99.849) Prec@5 100.000 (99.975)
Train Epoch: [46][41/47],lr: 0.00001 Loss 0.0120 (0.0237) Prec@1 100.000 (99.886) Prec@5 100.000 (99.981)
Train Epoch: [46][47/47],lr: 0.00001 Loss 0.0193 (0.0234) Prec@1 100.000 (99.883) Prec@5 100.000 (99.983)
Val Epoch: [46][1/46] Loss 0.5998 (0.5998)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.773 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [46][11/46] Loss 0.5960 (0.8224)
Cls@1:0.787 Cls@5:0.952
Loc@1:0.678 Loc@5:0.820 Loc_gt:0.861

Val Epoch: [46][21/46] Loss 0.6468 (0.7686)
Cls@1:0.807 Cls@5:0.951
Loc@1:0.711 Loc@5:0.836 Loc_gt:0.876

Val Epoch: [46][31/46] Loss 1.1760 (0.8654)
Cls@1:0.789 Cls@5:0.942
Loc@1:0.695 Loc@5:0.827 Loc_gt:0.874

Val Epoch: [46][41/46] Loss 1.0729 (0.8535)
Cls@1:0.793 Cls@5:0.944
Loc@1:0.691 Loc@5:0.823 Loc_gt:0.866

Val Epoch: [46][46/46] Loss 0.1534 (0.8234)
Cls@1:0.802 Cls@5:0.946
Loc@1:0.700 Loc@5:0.826 Loc_gt:0.867

wrong_details:4056 1149 0 461 126 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-18
Train Epoch: [47][1/47],lr: 0.00001 Loss 0.0396 (0.0396) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [47][11/47],lr: 0.00001 Loss 0.0295 (0.0252) Prec@1 99.219 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [47][21/47],lr: 0.00001 Loss 0.0518 (0.0237) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [47][31/47],lr: 0.00001 Loss 0.0085 (0.0246) Prec@1 100.000 (99.849) Prec@5 100.000 (100.000)
Train Epoch: [47][41/47],lr: 0.00001 Loss 0.0227 (0.0265) Prec@1 100.000 (99.829) Prec@5 100.000 (100.000)
Train Epoch: [47][47/47],lr: 0.00001 Loss 0.0144 (0.0249) Prec@1 100.000 (99.850) Prec@5 100.000 (100.000)
Val Epoch: [47][1/46] Loss 0.6034 (0.6034)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [47][11/46] Loss 0.5785 (0.8179)
Cls@1:0.791 Cls@5:0.948
Loc@1:0.681 Loc@5:0.818 Loc_gt:0.860

Val Epoch: [47][21/46] Loss 0.6566 (0.7673)
Cls@1:0.809 Cls@5:0.949
Loc@1:0.714 Loc@5:0.836 Loc_gt:0.878

Val Epoch: [47][31/46] Loss 1.1737 (0.8667)
Cls@1:0.790 Cls@5:0.941
Loc@1:0.696 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [47][41/46] Loss 1.0388 (0.8528)
Cls@1:0.793 Cls@5:0.944
Loc@1:0.693 Loc@5:0.825 Loc_gt:0.867

Val Epoch: [47][46/46] Loss 0.1526 (0.8228)
Cls@1:0.803 Cls@5:0.946
Loc@1:0.702 Loc@5:0.827 Loc_gt:0.868

wrong_details:4065 1143 0 454 130 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-21
Train Epoch: [48][1/47],lr: 0.00001 Loss 0.0160 (0.0160) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [48][11/47],lr: 0.00001 Loss 0.0348 (0.0211) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [48][21/47],lr: 0.00001 Loss 0.0494 (0.0246) Prec@1 100.000 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [48][31/47],lr: 0.00001 Loss 0.0188 (0.0234) Prec@1 100.000 (99.849) Prec@5 100.000 (100.000)
Train Epoch: [48][41/47],lr: 0.00001 Loss 0.0236 (0.0229) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Train Epoch: [48][47/47],lr: 0.00001 Loss 0.0106 (0.0229) Prec@1 100.000 (99.833) Prec@5 100.000 (100.000)
Val Epoch: [48][1/46] Loss 0.5971 (0.5971)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.773 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [48][11/46] Loss 0.5817 (0.8165)
Cls@1:0.793 Cls@5:0.950
Loc@1:0.682 Loc@5:0.817 Loc_gt:0.859

Val Epoch: [48][21/46] Loss 0.6472 (0.7662)
Cls@1:0.812 Cls@5:0.951
Loc@1:0.716 Loc@5:0.835 Loc_gt:0.877

Val Epoch: [48][31/46] Loss 1.1745 (0.8653)
Cls@1:0.793 Cls@5:0.941
Loc@1:0.698 Loc@5:0.827 Loc_gt:0.874

Val Epoch: [48][41/46] Loss 1.0508 (0.8520)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.695 Loc@5:0.824 Loc_gt:0.867

Val Epoch: [48][46/46] Loss 0.1401 (0.8221)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.703 Loc@5:0.826 Loc_gt:0.868

wrong_details:4075 1133 0 452 131 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-24
Train Epoch: [49][1/47],lr: 0.00001 Loss 0.0175 (0.0175) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [49][11/47],lr: 0.00001 Loss 0.0353 (0.0198) Prec@1 99.219 (99.716) Prec@5 100.000 (100.000)
Train Epoch: [49][21/47],lr: 0.00001 Loss 0.0149 (0.0204) Prec@1 100.000 (99.740) Prec@5 100.000 (100.000)
Train Epoch: [49][31/47],lr: 0.00001 Loss 0.0310 (0.0225) Prec@1 99.219 (99.748) Prec@5 100.000 (100.000)
Train Epoch: [49][41/47],lr: 0.00001 Loss 0.0207 (0.0231) Prec@1 100.000 (99.771) Prec@5 100.000 (100.000)
Train Epoch: [49][47/47],lr: 0.00001 Loss 0.0083 (0.0223) Prec@1 100.000 (99.800) Prec@5 100.000 (100.000)
Val Epoch: [49][1/46] Loss 0.5883 (0.5883)
Cls@1:0.844 Cls@5:0.969
Loc@1:0.773 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [49][11/46] Loss 0.5826 (0.8208)
Cls@1:0.791 Cls@5:0.947
Loc@1:0.682 Loc@5:0.817 Loc_gt:0.861

Val Epoch: [49][21/46] Loss 0.6578 (0.7707)
Cls@1:0.811 Cls@5:0.949
Loc@1:0.716 Loc@5:0.835 Loc_gt:0.878

Val Epoch: [49][31/46] Loss 1.1553 (0.8666)
Cls@1:0.793 Cls@5:0.940
Loc@1:0.699 Loc@5:0.826 Loc_gt:0.874

Val Epoch: [49][41/46] Loss 1.0411 (0.8528)
Cls@1:0.796 Cls@5:0.943
Loc@1:0.695 Loc@5:0.823 Loc_gt:0.867

Val Epoch: [49][46/46] Loss 0.1259 (0.8227)
Cls@1:0.804 Cls@5:0.945
Loc@1:0.703 Loc@5:0.826 Loc_gt:0.868

wrong_details:4075 1135 0 445 137 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-27
Train Epoch: [50][1/47],lr: 0.00001 Loss 0.0536 (0.0536) Prec@1 98.438 (98.438) Prec@5 100.000 (100.000)
Train Epoch: [50][11/47],lr: 0.00001 Loss 0.0086 (0.0331) Prec@1 100.000 (99.503) Prec@5 100.000 (100.000)
Train Epoch: [50][21/47],lr: 0.00001 Loss 0.0355 (0.0274) Prec@1 99.219 (99.665) Prec@5 100.000 (100.000)
Train Epoch: [50][31/47],lr: 0.00001 Loss 0.0111 (0.0249) Prec@1 100.000 (99.748) Prec@5 100.000 (99.975)
Train Epoch: [50][41/47],lr: 0.00001 Loss 0.0312 (0.0244) Prec@1 99.219 (99.771) Prec@5 100.000 (99.981)
Train Epoch: [50][47/47],lr: 0.00001 Loss 0.0113 (0.0258) Prec@1 100.000 (99.783) Prec@5 100.000 (99.983)
Val Epoch: [50][1/46] Loss 0.5870 (0.5870)
Cls@1:0.844 Cls@5:0.969
Loc@1:0.781 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [50][11/46] Loss 0.5833 (0.8194)
Cls@1:0.787 Cls@5:0.950
Loc@1:0.677 Loc@5:0.817 Loc_gt:0.859

Val Epoch: [50][21/46] Loss 0.6838 (0.7730)
Cls@1:0.809 Cls@5:0.950
Loc@1:0.714 Loc@5:0.835 Loc_gt:0.878

Val Epoch: [50][31/46] Loss 1.1676 (0.8704)
Cls@1:0.791 Cls@5:0.940
Loc@1:0.698 Loc@5:0.827 Loc_gt:0.874

Val Epoch: [50][41/46] Loss 1.0489 (0.8554)
Cls@1:0.795 Cls@5:0.943
Loc@1:0.696 Loc@5:0.824 Loc_gt:0.868

Val Epoch: [50][46/46] Loss 0.1341 (0.8255)
Cls@1:0.803 Cls@5:0.945
Loc@1:0.704 Loc@5:0.827 Loc_gt:0.869

wrong_details:4078 1140 0 437 136 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-32
Train Epoch: [51][1/47],lr: 0.00001 Loss 0.0878 (0.0878) Prec@1 99.219 (99.219) Prec@5 99.219 (99.219)
Train Epoch: [51][11/47],lr: 0.00001 Loss 0.0354 (0.0277) Prec@1 100.000 (99.787) Prec@5 100.000 (99.929)
Train Epoch: [51][21/47],lr: 0.00001 Loss 0.0140 (0.0242) Prec@1 100.000 (99.814) Prec@5 100.000 (99.963)
Train Epoch: [51][31/47],lr: 0.00001 Loss 0.0103 (0.0228) Prec@1 100.000 (99.824) Prec@5 100.000 (99.975)
Train Epoch: [51][41/47],lr: 0.00001 Loss 0.0248 (0.0233) Prec@1 99.219 (99.829) Prec@5 100.000 (99.981)
Train Epoch: [51][47/47],lr: 0.00001 Loss 0.0173 (0.0236) Prec@1 100.000 (99.850) Prec@5 100.000 (99.983)
Val Epoch: [51][1/46] Loss 0.5870 (0.5870)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [51][11/46] Loss 0.5853 (0.8185)
Cls@1:0.789 Cls@5:0.949
Loc@1:0.682 Loc@5:0.818 Loc_gt:0.862

Val Epoch: [51][21/46] Loss 0.6515 (0.7696)
Cls@1:0.810 Cls@5:0.949
Loc@1:0.716 Loc@5:0.836 Loc_gt:0.879

Val Epoch: [51][31/46] Loss 1.1635 (0.8656)
Cls@1:0.792 Cls@5:0.941
Loc@1:0.700 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [51][41/46] Loss 1.0549 (0.8526)
Cls@1:0.795 Cls@5:0.944
Loc@1:0.696 Loc@5:0.826 Loc_gt:0.869

Val Epoch: [51][46/46] Loss 0.1418 (0.8225)
Cls@1:0.803 Cls@5:0.946
Loc@1:0.703 Loc@5:0.828 Loc_gt:0.869

wrong_details:4076 1143 0 440 132 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-34
Train Epoch: [52][1/47],lr: 0.00001 Loss 0.0094 (0.0094) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [52][11/47],lr: 0.00001 Loss 0.0501 (0.0181) Prec@1 99.219 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [52][21/47],lr: 0.00001 Loss 0.0158 (0.0162) Prec@1 100.000 (99.926) Prec@5 100.000 (100.000)
Train Epoch: [52][31/47],lr: 0.00001 Loss 0.0194 (0.0208) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [52][41/47],lr: 0.00001 Loss 0.0108 (0.0191) Prec@1 100.000 (99.905) Prec@5 100.000 (100.000)
Train Epoch: [52][47/47],lr: 0.00001 Loss 0.0467 (0.0196) Prec@1 100.000 (99.917) Prec@5 100.000 (100.000)
Val Epoch: [52][1/46] Loss 0.5894 (0.5894)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [52][11/46] Loss 0.5834 (0.8176)
Cls@1:0.791 Cls@5:0.950
Loc@1:0.682 Loc@5:0.818 Loc_gt:0.861

Val Epoch: [52][21/46] Loss 0.6452 (0.7694)
Cls@1:0.811 Cls@5:0.949
Loc@1:0.716 Loc@5:0.835 Loc_gt:0.878

Val Epoch: [52][31/46] Loss 1.1875 (0.8670)
Cls@1:0.792 Cls@5:0.940
Loc@1:0.699 Loc@5:0.828 Loc_gt:0.876

Val Epoch: [52][41/46] Loss 1.0537 (0.8537)
Cls@1:0.795 Cls@5:0.943
Loc@1:0.697 Loc@5:0.826 Loc_gt:0.871

Val Epoch: [52][46/46] Loss 0.1482 (0.8236)
Cls@1:0.803 Cls@5:0.945
Loc@1:0.705 Loc@5:0.829 Loc_gt:0.871

wrong_details:4087 1139 0 426 140 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-39
Train Epoch: [53][1/47],lr: 0.00001 Loss 0.0145 (0.0145) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [53][11/47],lr: 0.00001 Loss 0.0212 (0.0190) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [53][21/47],lr: 0.00001 Loss 0.0136 (0.0187) Prec@1 100.000 (99.926) Prec@5 100.000 (100.000)
Train Epoch: [53][31/47],lr: 0.00001 Loss 0.0130 (0.0217) Prec@1 100.000 (99.849) Prec@5 100.000 (100.000)
Train Epoch: [53][41/47],lr: 0.00001 Loss 0.0131 (0.0208) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Train Epoch: [53][47/47],lr: 0.00001 Loss 0.0665 (0.0218) Prec@1 98.113 (99.816) Prec@5 99.057 (99.983)
Val Epoch: [53][1/46] Loss 0.6026 (0.6026)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.781 Loc@5:0.898 Loc_gt:0.930

Val Epoch: [53][11/46] Loss 0.5865 (0.8228)
Cls@1:0.790 Cls@5:0.949
Loc@1:0.680 Loc@5:0.816 Loc_gt:0.859

Val Epoch: [53][21/46] Loss 0.6295 (0.7703)
Cls@1:0.811 Cls@5:0.949
Loc@1:0.716 Loc@5:0.836 Loc_gt:0.879

Val Epoch: [53][31/46] Loss 1.1968 (0.8676)
Cls@1:0.794 Cls@5:0.941
Loc@1:0.701 Loc@5:0.828 Loc_gt:0.876

Val Epoch: [53][41/46] Loss 1.0906 (0.8547)
Cls@1:0.797 Cls@5:0.943
Loc@1:0.699 Loc@5:0.827 Loc_gt:0.871

Val Epoch: [53][46/46] Loss 0.1649 (0.8247)
Cls@1:0.805 Cls@5:0.945
Loc@1:0.707 Loc@5:0.829 Loc_gt:0.871

wrong_details:4097 1129 0 430 136 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-42
Train Epoch: [54][1/47],lr: 0.00001 Loss 0.0101 (0.0101) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [54][11/47],lr: 0.00001 Loss 0.0124 (0.0200) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [54][21/47],lr: 0.00001 Loss 0.0135 (0.0233) Prec@1 100.000 (99.851) Prec@5 100.000 (100.000)
Train Epoch: [54][31/47],lr: 0.00001 Loss 0.0102 (0.0201) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [54][41/47],lr: 0.00001 Loss 0.0101 (0.0214) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Train Epoch: [54][47/47],lr: 0.00001 Loss 0.0346 (0.0226) Prec@1 99.057 (99.816) Prec@5 100.000 (100.000)
Val Epoch: [54][1/46] Loss 0.5993 (0.5993)
Cls@1:0.859 Cls@5:0.969
Loc@1:0.797 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [54][11/46] Loss 0.5918 (0.8201)
Cls@1:0.790 Cls@5:0.950
Loc@1:0.683 Loc@5:0.819 Loc_gt:0.861

Val Epoch: [54][21/46] Loss 0.6591 (0.7699)
Cls@1:0.811 Cls@5:0.950
Loc@1:0.717 Loc@5:0.837 Loc_gt:0.879

Val Epoch: [54][31/46] Loss 1.1795 (0.8677)
Cls@1:0.792 Cls@5:0.942
Loc@1:0.699 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [54][41/46] Loss 1.0580 (0.8544)
Cls@1:0.796 Cls@5:0.944
Loc@1:0.698 Loc@5:0.827 Loc_gt:0.870

Val Epoch: [54][46/46] Loss 0.1541 (0.8240)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.706 Loc@5:0.829 Loc_gt:0.870

wrong_details:4090 1134 0 428 140 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-46
Train Epoch: [55][1/47],lr: 0.00001 Loss 0.0308 (0.0308) Prec@1 99.219 (99.219) Prec@5 100.000 (100.000)
Train Epoch: [55][11/47],lr: 0.00001 Loss 0.0188 (0.0299) Prec@1 100.000 (99.432) Prec@5 100.000 (100.000)
Train Epoch: [55][21/47],lr: 0.00001 Loss 0.0123 (0.0274) Prec@1 100.000 (99.591) Prec@5 100.000 (100.000)
Train Epoch: [55][31/47],lr: 0.00001 Loss 0.0197 (0.0256) Prec@1 100.000 (99.698) Prec@5 100.000 (100.000)
Train Epoch: [55][41/47],lr: 0.00001 Loss 0.0212 (0.0233) Prec@1 100.000 (99.771) Prec@5 100.000 (100.000)
Train Epoch: [55][47/47],lr: 0.00001 Loss 0.0185 (0.0229) Prec@1 100.000 (99.800) Prec@5 100.000 (100.000)
Val Epoch: [55][1/46] Loss 0.5915 (0.5915)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [55][11/46] Loss 0.5816 (0.8187)
Cls@1:0.786 Cls@5:0.951
Loc@1:0.680 Loc@5:0.822 Loc_gt:0.864

Val Epoch: [55][21/46] Loss 0.6688 (0.7698)
Cls@1:0.809 Cls@5:0.951
Loc@1:0.715 Loc@5:0.838 Loc_gt:0.879

Val Epoch: [55][31/46] Loss 1.1715 (0.8689)
Cls@1:0.790 Cls@5:0.942
Loc@1:0.698 Loc@5:0.830 Loc_gt:0.876

Val Epoch: [55][41/46] Loss 1.0606 (0.8555)
Cls@1:0.795 Cls@5:0.944
Loc@1:0.697 Loc@5:0.828 Loc_gt:0.870

Val Epoch: [55][46/46] Loss 0.1564 (0.8247)
Cls@1:0.804 Cls@5:0.946
Loc@1:0.706 Loc@5:0.830 Loc_gt:0.871

wrong_details:4091 1138 0 422 141 2
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-50
Train Epoch: [56][1/47],lr: 0.00001 Loss 0.0271 (0.0271) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [56][11/47],lr: 0.00001 Loss 0.0126 (0.0180) Prec@1 100.000 (99.858) Prec@5 100.000 (100.000)
Train Epoch: [56][21/47],lr: 0.00001 Loss 0.0542 (0.0268) Prec@1 98.438 (99.777) Prec@5 100.000 (100.000)
Train Epoch: [56][31/47],lr: 0.00001 Loss 0.0116 (0.0281) Prec@1 100.000 (99.798) Prec@5 100.000 (100.000)
Train Epoch: [56][41/47],lr: 0.00001 Loss 0.0482 (0.0262) Prec@1 98.438 (99.809) Prec@5 100.000 (100.000)
Train Epoch: [56][47/47],lr: 0.00001 Loss 0.0278 (0.0261) Prec@1 100.000 (99.833) Prec@5 100.000 (100.000)
Val Epoch: [56][1/46] Loss 0.5809 (0.5809)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [56][11/46] Loss 0.5742 (0.8242)
Cls@1:0.790 Cls@5:0.950
Loc@1:0.684 Loc@5:0.823 Loc_gt:0.866

Val Epoch: [56][21/46] Loss 0.6768 (0.7737)
Cls@1:0.811 Cls@5:0.951
Loc@1:0.719 Loc@5:0.840 Loc_gt:0.883

Val Epoch: [56][31/46] Loss 1.1830 (0.8676)
Cls@1:0.793 Cls@5:0.942
Loc@1:0.702 Loc@5:0.833 Loc_gt:0.880

Val Epoch: [56][41/46] Loss 1.0650 (0.8554)
Cls@1:0.797 Cls@5:0.944
Loc@1:0.701 Loc@5:0.830 Loc_gt:0.873

Val Epoch: [56][46/46] Loss 0.1398 (0.8244)
Cls@1:0.806 Cls@5:0.947
Loc@1:0.710 Loc@5:0.833 Loc_gt:0.874

wrong_details:4112 1125 0 422 131 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-52
Train Epoch: [57][1/47],lr: 0.00001 Loss 0.0199 (0.0199) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [57][11/47],lr: 0.00001 Loss 0.0171 (0.0235) Prec@1 100.000 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [57][21/47],lr: 0.00001 Loss 0.0217 (0.0234) Prec@1 100.000 (99.814) Prec@5 100.000 (100.000)
Train Epoch: [57][31/47],lr: 0.00001 Loss 0.0136 (0.0212) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [57][41/47],lr: 0.00001 Loss 0.0305 (0.0227) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [57][47/47],lr: 0.00001 Loss 0.0082 (0.0225) Prec@1 100.000 (99.850) Prec@5 100.000 (100.000)
Val Epoch: [57][1/46] Loss 0.6117 (0.6117)
Cls@1:0.844 Cls@5:0.969
Loc@1:0.781 Loc@5:0.906 Loc_gt:0.938

Val Epoch: [57][11/46] Loss 0.5685 (0.8312)
Cls@1:0.788 Cls@5:0.951
Loc@1:0.680 Loc@5:0.822 Loc_gt:0.864

Val Epoch: [57][21/46] Loss 0.6829 (0.7780)
Cls@1:0.810 Cls@5:0.952
Loc@1:0.716 Loc@5:0.839 Loc_gt:0.881

Val Epoch: [57][31/46] Loss 1.1750 (0.8711)
Cls@1:0.791 Cls@5:0.943
Loc@1:0.700 Loc@5:0.832 Loc_gt:0.878

Val Epoch: [57][41/46] Loss 1.0996 (0.8595)
Cls@1:0.795 Cls@5:0.944
Loc@1:0.699 Loc@5:0.829 Loc_gt:0.872

Val Epoch: [57][46/46] Loss 0.1241 (0.8284)
Cls@1:0.803 Cls@5:0.946
Loc@1:0.707 Loc@5:0.832 Loc_gt:0.873

wrong_details:4097 1142 0 418 133 4
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-21-57
Train Epoch: [58][1/47],lr: 0.00001 Loss 0.0199 (0.0199) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [58][11/47],lr: 0.00001 Loss 0.0069 (0.0166) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [58][21/47],lr: 0.00001 Loss 0.0121 (0.0187) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [58][31/47],lr: 0.00001 Loss 0.0236 (0.0200) Prec@1 100.000 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [58][41/47],lr: 0.00001 Loss 0.0080 (0.0199) Prec@1 100.000 (99.848) Prec@5 100.000 (100.000)
Train Epoch: [58][47/47],lr: 0.00001 Loss 0.0095 (0.0199) Prec@1 100.000 (99.833) Prec@5 100.000 (100.000)
Val Epoch: [58][1/46] Loss 0.6266 (0.6266)
Cls@1:0.852 Cls@5:0.969
Loc@1:0.789 Loc@5:0.906 Loc_gt:0.930

Val Epoch: [58][11/46] Loss 0.5957 (0.8278)
Cls@1:0.790 Cls@5:0.950
Loc@1:0.682 Loc@5:0.821 Loc_gt:0.864

Val Epoch: [58][21/46] Loss 0.6644 (0.7714)
Cls@1:0.812 Cls@5:0.952
Loc@1:0.719 Loc@5:0.839 Loc_gt:0.881

Val Epoch: [58][31/46] Loss 1.1754 (0.8653)
Cls@1:0.794 Cls@5:0.943
Loc@1:0.703 Loc@5:0.833 Loc_gt:0.878

Val Epoch: [58][41/46] Loss 1.0884 (0.8525)
Cls@1:0.797 Cls@5:0.945
Loc@1:0.700 Loc@5:0.829 Loc_gt:0.871

Val Epoch: [58][46/46] Loss 0.1423 (0.8218)
Cls@1:0.805 Cls@5:0.948
Loc@1:0.709 Loc@5:0.832 Loc_gt:0.872

wrong_details:4107 1127 0 424 131 5
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-22-00
Train Epoch: [59][1/47],lr: 0.00001 Loss 0.0150 (0.0150) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [59][11/47],lr: 0.00001 Loss 0.0192 (0.0229) Prec@1 99.219 (99.787) Prec@5 100.000 (100.000)
Train Epoch: [59][21/47],lr: 0.00001 Loss 0.0201 (0.0182) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [59][31/47],lr: 0.00001 Loss 0.0251 (0.0182) Prec@1 99.219 (99.874) Prec@5 100.000 (100.000)
Train Epoch: [59][41/47],lr: 0.00001 Loss 0.0259 (0.0175) Prec@1 100.000 (99.886) Prec@5 100.000 (100.000)
Train Epoch: [59][47/47],lr: 0.00001 Loss 0.0122 (0.0199) Prec@1 100.000 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [59][1/46] Loss 0.6290 (0.6290)
Cls@1:0.859 Cls@5:0.961
Loc@1:0.789 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [59][11/46] Loss 0.5950 (0.8164)
Cls@1:0.791 Cls@5:0.949
Loc@1:0.682 Loc@5:0.817 Loc_gt:0.861

Val Epoch: [59][21/46] Loss 0.6455 (0.7632)
Cls@1:0.815 Cls@5:0.951
Loc@1:0.720 Loc@5:0.836 Loc_gt:0.878

Val Epoch: [59][31/46] Loss 1.1943 (0.8623)
Cls@1:0.796 Cls@5:0.942
Loc@1:0.703 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [59][41/46] Loss 1.0612 (0.8514)
Cls@1:0.799 Cls@5:0.943
Loc@1:0.700 Loc@5:0.826 Loc_gt:0.870

Val Epoch: [59][46/46] Loss 0.1531 (0.8206)
Cls@1:0.807 Cls@5:0.946
Loc@1:0.709 Loc@5:0.829 Loc_gt:0.871

wrong_details:4109 1118 0 430 134 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-22-04
Train Epoch: [60][1/47],lr: 0.00000 Loss 0.0119 (0.0119) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000)
Train Epoch: [60][11/47],lr: 0.00000 Loss 0.0064 (0.0222) Prec@1 100.000 (99.929) Prec@5 100.000 (100.000)
Train Epoch: [60][21/47],lr: 0.00000 Loss 0.0258 (0.0265) Prec@1 100.000 (99.888) Prec@5 100.000 (100.000)
Train Epoch: [60][31/47],lr: 0.00000 Loss 0.0171 (0.0239) Prec@1 100.000 (99.899) Prec@5 100.000 (100.000)
Train Epoch: [60][41/47],lr: 0.00000 Loss 0.0145 (0.0230) Prec@1 100.000 (99.886) Prec@5 100.000 (100.000)
Train Epoch: [60][47/47],lr: 0.00000 Loss 0.0304 (0.0226) Prec@1 99.057 (99.867) Prec@5 100.000 (100.000)
Val Epoch: [60][1/46] Loss 0.6284 (0.6284)
Cls@1:0.859 Cls@5:0.961
Loc@1:0.789 Loc@5:0.891 Loc_gt:0.922

Val Epoch: [60][11/46] Loss 0.5946 (0.8180)
Cls@1:0.790 Cls@5:0.949
Loc@1:0.682 Loc@5:0.817 Loc_gt:0.862

Val Epoch: [60][21/46] Loss 0.6449 (0.7642)
Cls@1:0.815 Cls@5:0.951
Loc@1:0.721 Loc@5:0.837 Loc_gt:0.879

Val Epoch: [60][31/46] Loss 1.1920 (0.8629)
Cls@1:0.796 Cls@5:0.941
Loc@1:0.703 Loc@5:0.829 Loc_gt:0.876

Val Epoch: [60][41/46] Loss 1.0606 (0.8517)
Cls@1:0.799 Cls@5:0.943
Loc@1:0.700 Loc@5:0.826 Loc_gt:0.870

Val Epoch: [60][46/46] Loss 0.1511 (0.8209)
Cls@1:0.807 Cls@5:0.946
Loc@1:0.709 Loc@5:0.829 Loc_gt:0.871

wrong_details:4108 1117 0 433 133 3
Best GT_LOC: 0.8862616499827408
Best TOP1_LOC: 0.8862616499827408
2021-07-29-22-08