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nohup.out
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2020-04-10 15:26:29.686976: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-04-10 15:26:36.233418: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1405] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.582
pciBusID: 0000:04:00.0
totalMemory: 10.91GiB freeMemory: 10.75GiB
2020-04-10 15:26:36.233487: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2020-04-10 15:26:36.666468: I tensorflow/core/common_runtime/gpu/gpu_device.cc:965] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-04-10 15:26:36.666529: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0
2020-04-10 15:26:36.666539: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] 0: N
2020-04-10 15:26:36.666949: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1097] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10400 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:04:00.0, compute capability: 6.1)
/home/zhangjinyang/.local/lib/python3.5/site-packages/requests/__init__.py:83: RequestsDependencyWarning: Old version of cryptography ([1, 2, 3]) may cause slowdown.
warnings.warn(warning, RequestsDependencyWarning)
WARNING:tensorflow:From /home/zhangjinyang/.local/lib/python3.5/site-packages/tensorflow/python/framework/function.py:986: calling Graph.create_op (from tensorflow.python.framework.ops) with compute_shapes is deprecated and will be removed in a future version.
Instructions for updating:
Shapes are always computed; don't use the compute_shapes as it has no effect.
DataSet PaviaU shape is (610, 340, 103)
traindata-ID 1: 10; testdata-ID 1: 6621
traindata-ID 2: 10; testdata-ID 2: 18639
traindata-ID 3: 10; testdata-ID 3: 2089
traindata-ID 4: 10; testdata-ID 4: 3054
traindata-ID 5: 10; testdata-ID 5: 1335
traindata-ID 6: 10; testdata-ID 6: 5019
traindata-ID 7: 10; testdata-ID 7: 1320
traindata-ID 8: 10; testdata-ID 8: 3672
traindata-ID 9: 10; testdata-ID 9: 937
total train 90, total test 42686
Tensor("Placeholder_1:0", shape=(?, 3, 3, 103), dtype=float32)
Tensor("classifer/conv00/swish_f32:0", shape=(?, 1, 3, 32, 64), dtype=float32)
Tensor("classifer/conv01/swish_f32:0", shape=(?, 1, 3, 30, 64), dtype=float32)
Tensor("classifer/conv02/swish_f32:0", shape=(?, 1, 3, 30, 64), dtype=float32)
Tensor("classifer/conv10/swish_f32:0", shape=(?, 1, 1, 14, 128), dtype=float32)
Tensor("classifer/conv11/swish_f32:0", shape=(?, 1, 1, 12, 128), dtype=float32)
Tensor("classifer/conv12/swish_f32:0", shape=(?, 1, 1, 12, 128), dtype=float32)
Tensor("classifer/conv20/swish_f32:0", shape=(?, 1, 1, 5, 256), dtype=float32)
Tensor("classifer/conv21/swish_f32:0", shape=(?, 1, 1, 3, 256), dtype=float32)
Tensor("classifer/conv22/swish_f32:0", shape=(?, 1, 1, 3, 256), dtype=float32)
Tensor("classifer/global_info/flatten/Reshape:0", shape=(?, 512), dtype=float32)
step 1000, loss_cluster 0.084445 ,loss_classification 0.000126,loss_fusion 0.000105,loss_total 0.084677 lr 0.000990
step 2000, loss_cluster 0.003331 ,loss_classification 0.000039,loss_fusion 0.000029,loss_total 0.003399 lr 0.000979
step 3000, loss_cluster 0.020193 ,loss_classification 0.003424,loss_fusion 0.001793,loss_total 0.025410 lr 0.000969
step 4000, loss_cluster 0.013539 ,loss_classification 0.000013,loss_fusion 0.000005,loss_total 0.013557 lr 0.000959
step 5000, loss_cluster 0.000609 ,loss_classification 0.000002,loss_fusion 0.000002,loss_total 0.000614 lr 0.000949
4707 5000 0.9414
9163 10000 0.9163
13317 15000 0.8878
18043 20000 0.90215
22616 25000 0.90464
26448 30000 0.8816
31442 35000 0.8983428571428571
36014 40000 0.90035
38190 42686 0.8946727264208405
test end!
1 class: ( 6103.0 / 6621.0 ) 0.9217640839752304
2 class: ( 16761.0 / 18639.0 ) 0.8992435216481571
3 class: ( 941.0 / 2089.0 ) 0.4504547630445189
4 class: ( 3042.0 / 3054.0 ) 0.9960707269155207
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5017.0 / 5019.0 ) 0.9996015142458657
7 class: ( 1293.0 / 1320.0 ) 0.9795454545454545
8 class: ( 2761.0 / 3672.0 ) 0.7519063180827886
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6103 1 56 0 0 0 21 55 0]
[ 0 16761 285 11 0 1 0 64 0]
[ 0 0 941 0 0 0 0 152 0]
[ 0 4 0 3042 0 1 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 502 1872 8 1 0 5017 6 640 0]
[ 15 0 0 0 0 0 1293 0 0]
[ 1 1 799 0 0 0 0 2761 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 38190.0
oa: 0.8946727264208405
aa: 0.8887318202730595
kappa: 0.8621519995990607
best model saved...
best accuracy:0.894673
step 6000, loss_cluster 0.023412 ,loss_classification 0.000066,loss_fusion 0.000065,loss_total 0.023542 lr 0.000939
step 7000, loss_cluster 0.042101 ,loss_classification 0.000014,loss_fusion 0.000033,loss_total 0.042148 lr 0.000929
step 8000, loss_cluster 0.010895 ,loss_classification 0.000003,loss_fusion 0.000001,loss_total 0.010899 lr 0.000919
step 9000, loss_cluster 0.007822 ,loss_classification 0.000011,loss_fusion 0.000006,loss_total 0.007840 lr 0.000910
step 10000, loss_cluster 0.000517 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000518 lr 0.000900
4991 5000 0.9982
9973 10000 0.9973
14924 15000 0.9949333333333333
19924 20000 0.9962
24911 25000 0.99644
29734 30000 0.9911333333333333
34628 35000 0.9893714285714286
38575 40000 0.964375
41185 42686 0.9648362460759968
test end!
1 class: ( 6609.0 / 6621.0 ) 0.9981875849569551
2 class: ( 18561.0 / 18639.0 ) 0.9958152261387413
3 class: ( 1952.0 / 2089.0 ) 0.9344183820009574
4 class: ( 3013.0 / 3054.0 ) 0.9865749836280289
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4818.0 / 5019.0 ) 0.9599521817095039
7 class: ( 1299.0 / 1320.0 ) 0.9840909090909091
8 class: ( 2661.0 / 3672.0 ) 0.7246732026143791
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6609 0 0 0 0 0 20 0 0]
[ 0 18561 0 40 0 172 0 0 0]
[ 0 0 1952 0 0 0 0 1010 0]
[ 0 6 0 3013 0 18 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 2 23 0 0 0 4818 0 1 0]
[ 0 6 0 1 0 11 1299 0 0]
[ 10 43 137 0 0 0 1 2661 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 41185.0
oa: 0.9648362460759968
aa: 0.9537458300154972
kappa: 0.9533565540772628
best model saved...
best accuracy:0.964836
step 11000, loss_cluster 0.000264 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000264 lr 0.000891
step 12000, loss_cluster 0.011954 ,loss_classification 0.000014,loss_fusion 0.000014,loss_total 0.011982 lr 0.000881
step 13000, loss_cluster 0.000913 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000914 lr 0.000872
step 14000, loss_cluster 0.013507 ,loss_classification 0.000001,loss_fusion 0.000001,loss_total 0.013509 lr 0.000863
step 15000, loss_cluster 0.006051 ,loss_classification 0.000001,loss_fusion 0.000001,loss_total 0.006053 lr 0.000854
4856 5000 0.9712
9714 10000 0.9714
12304 15000 0.8202666666666667
13534 20000 0.6767
15890 25000 0.6356
20770 30000 0.6923333333333334
25770 35000 0.7362857142857143
29918 40000 0.74795
32381 42686 0.7585859532399382
test end!
1 class: ( 6470.0 / 6621.0 ) 0.9771937773750189
2 class: ( 9562.0 / 18639.0 ) 0.5130103546327592
3 class: ( 2087.0 / 2089.0 ) 0.9990426041168023
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1312.0 / 1320.0 ) 0.9939393939393939
8 class: ( 2605.0 / 3672.0 ) 0.7094226579520697
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[6470 0 1 0 0 0 8 21 0]
[ 0 9562 0 0 0 0 0 0 0]
[ 130 0 2087 0 0 0 0 1025 0]
[ 0 1979 0 3054 0 0 0 0 0]
[ 2 0 0 0 1335 0 0 0 0]
[ 12 7095 0 0 0 5019 0 21 0]
[ 3 0 0 0 0 0 1312 0 0]
[ 0 3 1 0 0 0 0 2605 0]
[ 4 0 0 0 0 0 0 0 937]]
total right num: 32381.0
oa: 0.7585859532399382
aa: 0.9102898653351161
kappa: 0.7074765783761165
best accuracy:0.964836
step 16000, loss_cluster 0.000239 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000239 lr 0.000845
step 17000, loss_cluster 0.000066 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000067 lr 0.000836
step 18000, loss_cluster 0.001095 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.001095 lr 0.000827
step 19000, loss_cluster 0.000493 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000493 lr 0.000819
step 20000, loss_cluster 0.000359 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000359 lr 0.000810
4989 5000 0.9978
9979 10000 0.9979
14976 15000 0.9984
19976 20000 0.9988
24976 25000 0.99904
29908 30000 0.9969333333333333
34669 35000 0.9905428571428572
38822 40000 0.97055
41476 42686 0.971653469521623
test end!
1 class: ( 6601.0 / 6621.0 ) 0.9969793082615919
2 class: ( 18635.0 / 18639.0 ) 0.9997853962122432
3 class: ( 2085.0 / 2089.0 ) 0.9980852082336046
4 class: ( 2982.0 / 3054.0 ) 0.9764243614931237
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4690.0 / 5019.0 ) 0.9344490934449093
7 class: ( 1317.0 / 1320.0 ) 0.9977272727272727
8 class: ( 2894.0 / 3672.0 ) 0.7881263616557734
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6601 0 0 0 0 0 0 0 0]
[ 0 18635 0 60 0 308 0 0 0]
[ 4 0 2085 0 0 0 0 778 0]
[ 0 0 0 2982 0 1 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 2 3 0 0 0 4690 0 0 0]
[ 3 0 0 0 0 0 1317 0 0]
[ 11 1 4 0 0 20 3 2894 0]
[ 0 0 0 12 0 0 0 0 937]]
total right num: 41476.0
oa: 0.971653469521623
aa: 0.9657307780031688
kappa: 0.962308723213576
best model saved...
best accuracy:0.971653
step 21000, loss_cluster 0.000951 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000951 lr 0.000802
step 22000, loss_cluster 0.000088 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000088 lr 0.000793
step 23000, loss_cluster 0.002221 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.002221 lr 0.000785
step 24000, loss_cluster 0.000737 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000737 lr 0.000777
step 25000, loss_cluster 0.045093 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.045093 lr 0.000768
4983 5000 0.9966
9963 10000 0.9963
14960 15000 0.9973333333333333
19960 20000 0.998
24952 25000 0.99808
29947 30000 0.9982333333333333
34714 35000 0.9918285714285714
39042 40000 0.97605
41721 42686 0.9773930562713771
test end!
1 class: ( 6594.0 / 6621.0 ) 0.995922066153149
2 class: ( 18618.0 / 18639.0 ) 0.9988733301142765
3 class: ( 2085.0 / 2089.0 ) 0.9980852082336046
4 class: ( 3053.0 / 3054.0 ) 0.9996725605762934
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4493.0 / 5019.0 ) 0.8951982466626818
7 class: ( 1301.0 / 1320.0 ) 0.9856060606060606
8 class: ( 3305.0 / 3672.0 ) 0.9000544662309368
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6594 0 0 0 0 20 9 0 0]
[ 0 18618 0 1 0 493 0 0 0]
[ 8 0 2085 0 0 0 0 359 0]
[ 0 3 0 3053 0 0 0 0 0]
[ 0 2 0 0 1335 0 0 0 0]
[ 1 4 0 0 0 4493 0 0 0]
[ 0 0 0 0 0 0 1301 8 0]
[ 18 12 4 0 0 12 9 3305 0]
[ 0 0 0 0 0 1 1 0 937]]
total right num: 41721.0
oa: 0.9773930562713771
aa: 0.974823548730778
kappa: 0.969894483611018
best model saved...
best accuracy:0.977393
step 26000, loss_cluster 0.000275 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000275 lr 0.000760
step 27000, loss_cluster 0.017271 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.017272 lr 0.000752
step 28000, loss_cluster 0.000127 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000127 lr 0.000745
step 29000, loss_cluster 0.000212 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000212 lr 0.000737
step 30000, loss_cluster 0.000439 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000439 lr 0.000729
4999 5000 0.9998
9998 10000 0.9998
14939 15000 0.9959333333333333
19901 20000 0.99505
24848 25000 0.99392
29847 30000 0.9949
34847 35000 0.9956285714285714
38818 40000 0.97045
41392 42686 0.9696856112074216
test end!
1 class: ( 6620.0 / 6621.0 ) 0.9998489654130795
2 class: ( 18487.0 / 18639.0 ) 0.9918450560652395
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1314.0 / 1320.0 ) 0.9954545454545455
8 class: ( 2537.0 / 3672.0 ) 0.6909041394335512
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6620 0 0 0 0 0 0 0 0]
[ 0 18487 0 0 0 0 0 0 0]
[ 1 0 2089 0 0 0 0 1135 0]
[ 0 10 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 137 0 0 0 5019 1 0 0]
[ 0 0 0 0 0 0 1314 0 0]
[ 0 5 0 0 0 0 5 2537 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 41392.0
oa: 0.9696856112074216
aa: 0.9642280784851572
kappa: 0.959914875911596
best accuracy:0.977393
step 31000, loss_cluster 0.000368 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000368 lr 0.000721
step 32000, loss_cluster 0.000059 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000059 lr 0.000714
step 33000, loss_cluster 0.000062 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000062 lr 0.000706
step 34000, loss_cluster 0.000020 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000020 lr 0.000699
step 35000, loss_cluster 0.000029 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000029 lr 0.000692
4994 5000 0.9988
9959 10000 0.9959
14926 15000 0.9950666666666667
19926 20000 0.9963
24918 25000 0.99672
29912 30000 0.9970666666666667
34912 35000 0.9974857142857143
39171 40000 0.979275
41834 42686 0.9800402942416717
test end!
1 class: ( 6606.0 / 6621.0 ) 0.9977344811961939
2 class: ( 18571.0 / 18639.0 ) 0.9963517356081335
3 class: ( 2084.0 / 2089.0 ) 0.9976065102920058
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1316.0 / 1320.0 ) 0.996969696969697
8 class: ( 2913.0 / 3672.0 ) 0.7933006535947712
9 class: ( 936.0 / 937.0 ) 0.9989327641408752
confusion matrix:
[[ 6606 0 0 0 0 0 2 1 1]
[ 0 18571 0 0 0 0 0 0 0]
[ 0 2 2084 0 0 0 0 757 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 3 0 0 1335 0 0 0 0]
[ 4 60 0 0 0 5019 1 1 0]
[ 4 0 0 0 0 0 1316 0 0]
[ 7 1 5 0 0 0 1 2913 0]
[ 0 2 0 0 0 0 0 0 936]]
total right num: 41834.0
oa: 0.9800402942416717
aa: 0.9756550935335196
kappa: 0.9735740696784885
best model saved...
best accuracy:0.980040
step 36000, loss_cluster 0.000098 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000098 lr 0.000684
step 37000, loss_cluster 0.000016 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000016 lr 0.000677
step 38000, loss_cluster 0.000173 ,loss_classification 0.000002,loss_fusion 0.000000,loss_total 0.000175 lr 0.000670
step 39000, loss_cluster 0.000037 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000037 lr 0.000663
step 40000, loss_cluster 0.002106 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.002106 lr 0.000656
4999 5000 0.9998
9994 10000 0.9994
14984 15000 0.9989333333333333
19976 20000 0.9988
24968 25000 0.99872
29950 30000 0.9983333333333333
34762 35000 0.9932
39529 40000 0.988225
42203 42686 0.9886848146933421
test end!
1 class: ( 6620.0 / 6621.0 ) 0.9998489654130795
2 class: ( 18608.0 / 18639.0 ) 0.9983368206448844
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3036.0 / 3054.0 ) 0.9941060903732809
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4701.0 / 5019.0 ) 0.9366407650926479
7 class: ( 1317.0 / 1320.0 ) 0.9977272727272727
8 class: ( 3560.0 / 3672.0 ) 0.9694989106753813
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6620 0 0 0 0 22 1 0 0]
[ 0 18608 0 0 0 246 0 0 0]
[ 0 1 2089 0 0 41 0 84 0]
[ 0 23 0 3036 0 0 0 0 0]
[ 0 0 0 0 1335 7 0 0 0]
[ 1 7 0 0 0 4701 2 0 0]
[ 0 0 0 0 0 0 1317 28 0]
[ 0 0 0 0 0 0 0 3560 0]
[ 0 0 0 18 0 2 0 0 937]]
total right num: 42203.0
oa: 0.9886848146933421
aa: 0.9884620916585052
kappa: 0.9849677650135389
best model saved...
best accuracy:0.988685
step 41000, loss_cluster 0.000049 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000049 lr 0.000649
step 42000, loss_cluster 0.000012 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000012 lr 0.000642
step 43000, loss_cluster 0.000142 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000142 lr 0.000636
step 44000, loss_cluster 0.000012 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000012 lr 0.000629
step 45000, loss_cluster 0.053863 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.053863 lr 0.000622
4997 5000 0.9994
9991 10000 0.9991
14939 15000 0.9959333333333333
19919 20000 0.99595
24824 25000 0.99296
29673 30000 0.9891
34624 35000 0.9892571428571428
39349 40000 0.983725
42026 42686 0.9845382561027035
test end!
1 class: ( 6616.0 / 6621.0 ) 0.999244827065398
2 class: ( 18460.0 / 18639.0 ) 0.9903964804978808
3 class: ( 1946.0 / 2089.0 ) 0.9315461943513643
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4908.0 / 5019.0 ) 0.9778840406455469
7 class: ( 1314.0 / 1320.0 ) 0.9954545454545455
8 class: ( 3456.0 / 3672.0 ) 0.9411764705882353
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6616 0 0 0 0 0 0 7 0]
[ 0 18460 0 0 0 102 0 0 0]
[ 2 0 1946 0 0 0 0 203 0]
[ 0 92 0 3054 0 0 0 0 0]
[ 0 16 0 0 1335 9 0 0 0]
[ 3 69 0 0 0 4908 0 6 0]
[ 0 0 0 0 0 0 1314 0 0]
[ 0 2 143 0 0 0 6 3456 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 42026.0
oa: 0.9845382561027035
aa: 0.9817447287336635
kappa: 0.9795176852531933
best accuracy:0.988685
step 46000, loss_cluster 0.000007 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000007 lr 0.000616
step 47000, loss_cluster 0.000144 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000144 lr 0.000609
step 48000, loss_cluster 0.000004 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000004 lr 0.000603
step 49000, loss_cluster 0.000015 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000015 lr 0.000597
step 50000, loss_cluster 0.000642 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000642 lr 0.000590
4995 5000 0.999
9930 10000 0.993
14334 15000 0.9556
18885 20000 0.94425
23672 25000 0.94688
28649 30000 0.9549666666666666
33641 35000 0.9611714285714286
38500 40000 0.9625
41182 42686 0.9647659654219182
test end!
1 class: ( 6580.0 / 6621.0 ) 0.9938075819362634
2 class: ( 17329.0 / 18639.0 ) 0.9297172595096304
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5007.0 / 5019.0 ) 0.9976090854751942
7 class: ( 1320.0 / 1320.0 ) 1.0
8 class: ( 3531.0 / 3672.0 ) 0.9616013071895425
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6580 0 0 0 0 0 0 0 0]
[ 0 17329 0 0 0 0 0 0 0]
[ 0 1 2089 0 0 0 0 140 0]
[ 0 56 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 1125 0 0 0 5007 0 0 0]
[ 0 0 0 0 0 0 1320 1 0]
[ 41 128 0 0 0 12 0 3531 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 41182.0
oa: 0.9647659654219182
aa: 0.9869705815678478
kappa: 0.953898235977831
best accuracy:0.988685
step 51000, loss_cluster 0.000244 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000244 lr 0.000584
step 52000, loss_cluster 0.000207 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000207 lr 0.000578
step 53000, loss_cluster 0.000043 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000043 lr 0.000572
step 54000, loss_cluster 0.000022 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000022 lr 0.000566
step 55000, loss_cluster 0.000004 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000004 lr 0.000560
4999 5000 0.9998
9999 10000 0.9999
14999 15000 0.9999333333333333
19999 20000 0.99995
24999 25000 0.99996
29998 30000 0.9999333333333333
34998 35000 0.9999428571428571
39885 40000 0.997125
42571 42686 0.9973059082603195
test end!
1 class: ( 6620.0 / 6621.0 ) 0.9998489654130795
2 class: ( 18638.0 / 18639.0 ) 0.9999463490530608
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1318.0 / 1320.0 ) 0.9984848484848485
8 class: ( 3561.0 / 3672.0 ) 0.9697712418300654
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6620 0 0 0 0 0 0 0 0]
[ 0 18638 0 0 0 0 0 0 0]
[ 0 0 2089 0 0 0 0 109 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 1 0 0 0 5019 1 0 0]
[ 1 0 0 0 0 0 1318 2 0]
[ 0 0 0 0 0 0 1 3561 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 42571.0
oa: 0.9973059082603195
aa: 0.9964501560867838
kappa: 0.9964279949629802
best model saved...
best accuracy:0.997306
step 56000, loss_cluster 0.000003 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000003 lr 0.000554
step 57000, loss_cluster 0.000158 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000159 lr 0.000549
step 58000, loss_cluster 0.000009 ,loss_classification 0.000000,loss_fusion 0.000001,loss_total 0.000010 lr 0.000543
step 59000, loss_cluster 0.000089 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000089 lr 0.000537
step 60000, loss_cluster 0.000917 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000917 lr 0.000531
4978 5000 0.9956
9908 10000 0.9908
14825 15000 0.9883333333333333
19785 20000 0.98925
24744 25000 0.98976
29739 30000 0.9913
34739 35000 0.9925428571428572
39460 40000 0.9865
42115 42686 0.9866232488403692
test end!
1 class: ( 6530.0 / 6621.0 ) 0.9862558525902432
2 class: ( 18469.0 / 18639.0 ) 0.9908793390203338
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1320.0 / 1320.0 ) 1.0
8 class: ( 3362.0 / 3672.0 ) 0.9155773420479303
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6530 0 0 0 0 0 0 0 0]
[ 0 18469 0 0 0 0 0 0 0]
[ 2 0 2089 0 0 0 0 308 0]
[ 0 54 0 3054 0 0 0 0 0]
[ 0 2 0 0 1335 0 0 0 0]
[ 0 104 0 0 0 5019 0 0 0]
[ 0 0 0 0 0 0 1320 2 0]
[ 89 8 0 0 0 0 0 3362 0]
[ 0 2 0 0 0 0 0 0 937]]
total right num: 42115.0
oa: 0.9866232488403692
aa: 0.9880791704065008
kappa: 0.9823031271444916
best accuracy:0.997306
step 61000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000526
step 62000, loss_cluster 0.000003 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000003 lr 0.000520
step 63000, loss_cluster 0.000386 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000386 lr 0.000515
step 64000, loss_cluster 0.000035 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000035 lr 0.000510
step 65000, loss_cluster 0.000012 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000012 lr 0.000504
4980 5000 0.996
8137 10000 0.8137
9576 15000 0.6384
10594 20000 0.5297
12244 25000 0.48976
17027 30000 0.5675666666666667
21401 35000 0.6114571428571428
24454 40000 0.61135
26495 42686 0.6206953099376845
test end!
1 class: ( 6476.0 / 6621.0 ) 0.9780999848965413
2 class: ( 5840.0 / 18639.0 ) 0.3133215301250067
3 class: ( 2060.0 / 2089.0 ) 0.9861177596936334
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 3993.0 / 5019.0 ) 0.7955768081291094
7 class: ( 1173.0 / 1320.0 ) 0.8886363636363637
8 class: ( 1627.0 / 3672.0 ) 0.44308278867102396
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[6476 30 28 0 0 12 146 492 0]
[ 0 5840 0 0 0 0 0 0 0]
[ 2 382 2060 0 0 0 0 1327 0]
[ 0 614 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 6749 0 0 0 3993 0 0 0]
[ 6 0 0 0 0 17 1173 226 0]
[ 137 5024 1 0 0 997 1 1627 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 26495.0
oa: 0.6206953099376845
aa: 0.8227594705724086
kappa: 0.5568415016386574
best accuracy:0.997306
step 66000, loss_cluster 0.000003 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000003 lr 0.000499
step 67000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000494
step 68000, loss_cluster 0.000012 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000012 lr 0.000488
step 69000, loss_cluster 0.000003 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000003 lr 0.000483
step 70000, loss_cluster 0.000309 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000309 lr 0.000478
4940 5000 0.988
9842 10000 0.9842
14606 15000 0.9737333333333333
19538 20000 0.9769
24380 25000 0.9752
29069 30000 0.9689666666666666
33984 35000 0.9709714285714286
37735 40000 0.943375
39446 42686 0.9240968935950897
test end!
1 class: ( 6473.0 / 6621.0 ) 0.9776468811357801
2 class: ( 18161.0 / 18639.0 ) 0.974354847363056
3 class: ( 1795.0 / 2089.0 ) 0.8592628051699378
4 class: ( 3043.0 / 3054.0 ) 0.9963981663392273
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4779.0 / 5019.0 ) 0.9521817095038853
7 class: ( 1315.0 / 1320.0 ) 0.9962121212121212
8 class: ( 1608.0 / 3672.0 ) 0.43790849673202614
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6473 0 95 0 0 0 2 132 0]
[ 0 18161 9 0 0 187 0 64 0]
[ 14 1 1795 1 0 1 0 468 0]
[ 0 22 0 3043 0 1 0 1 0]
[ 0 0 3 0 1335 4 0 154 0]
[ 114 430 89 0 0 4779 0 1236 0]
[ 18 0 0 0 0 0 1315 9 0]
[ 2 8 98 0 0 0 3 1608 0]
[ 0 17 0 10 0 47 0 0 937]]
total right num: 39446.0
oa: 0.9240968935950897
aa: 0.9104405586062261
kappa: 0.8994782351311251
best accuracy:0.997306
step 71000, loss_cluster 0.000020 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000020 lr 0.000473
step 72000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000468
step 73000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000463
step 74000, loss_cluster 0.000005 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000005 lr 0.000459
step 75000, loss_cluster 0.000114 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000114 lr 0.000454
4991 5000 0.9982
9972 10000 0.9972
14949 15000 0.9966
19835 20000 0.99175
24796 25000 0.99184
29795 30000 0.9931666666666666
34795 35000 0.9941428571428571
39616 40000 0.9904
42301 42686 0.9909806493932437
test end!
1 class: ( 6609.0 / 6621.0 ) 0.9981875849569551
2 class: ( 18446.0 / 18639.0 ) 0.9896453672407318
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1317.0 / 1320.0 ) 0.9977272727272727
8 class: ( 3495.0 / 3672.0 ) 0.951797385620915
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6609 0 0 0 0 0 0 0 0]
[ 0 18446 0 0 0 0 0 0 0]
[ 2 0 2089 0 0 0 0 173 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 191 0 0 0 5019 0 0 0]
[ 4 0 0 0 0 0 1317 4 0]
[ 6 0 0 0 0 0 3 3495 0]
[ 0 2 0 0 0 0 0 0 937]]
total right num: 42301.0
oa: 0.9909806493932437
aa: 0.9930397345050971
kappa: 0.988065611147455
best accuracy:0.997306
step 76000, loss_cluster 0.000006 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000006 lr 0.000449
step 77000, loss_cluster 0.000006 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000006 lr 0.000444
step 78000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000440
step 79000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000435
step 80000, loss_cluster 0.000004 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000004 lr 0.000430
4999 5000 0.9998
9998 10000 0.9998
14989 15000 0.9992666666666666
19988 20000 0.9994
24954 25000 0.99816
29950 30000 0.9983333333333333
34935 35000 0.9981428571428571
39587 40000 0.989675
42218 42686 0.9890362179637352
test end!
1 class: ( 6620.0 / 6621.0 ) 0.9998489654130795
2 class: ( 18591.0 / 18639.0 ) 0.9974247545469177
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3053.0 / 3054.0 ) 0.9996725605762934
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4963.0 / 5019.0 ) 0.9888423988842399
7 class: ( 1319.0 / 1320.0 ) 0.9992424242424243
8 class: ( 3311.0 / 3672.0 ) 0.9016884531590414
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6620 0 0 0 0 0 0 1 0]
[ 0 18591 0 0 0 55 0 1 0]
[ 1 0 2089 1 0 0 0 321 0]
[ 0 0 0 3053 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 27 0 0 0 4963 0 38 0]
[ 0 0 0 0 0 0 1319 0 0]
[ 0 0 0 0 0 0 1 3311 0]
[ 0 21 0 0 0 1 0 0 937]]
total right num: 42218.0
oa: 0.9890362179637352
aa: 0.9874132840913329
kappa: 0.9854660997726332
best accuracy:0.997306
step 81000, loss_cluster 0.000003 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000003 lr 0.000426
step 82000, loss_cluster 0.000005 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000005 lr 0.000421
step 83000, loss_cluster 0.000015 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000015 lr 0.000417
step 84000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000413
step 85000, loss_cluster 0.000024 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000024 lr 0.000408
4956 5000 0.9912
8129 10000 0.8129
8867 15000 0.5911333333333333
9196 20000 0.4598
9797 25000 0.39188
14333 30000 0.4777666666666667
18816 35000 0.5376
22906 40000 0.57265
25481 42686 0.5969404488591107
test end!
1 class: ( 6429.0 / 6621.0 ) 0.9710013593112823
2 class: ( 3392.0 / 18639.0 ) 0.1819840120178121
3 class: ( 1862.0 / 2089.0 ) 0.8913355672570608
4 class: ( 3053.0 / 3054.0 ) 0.9996725605762934
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 4189.0 / 5019.0 ) 0.8346284120342697
7 class: ( 1314.0 / 1320.0 ) 0.9954545454545455
8 class: ( 2970.0 / 3672.0 ) 0.8088235294117647
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[6429 2 14 0 0 1 5 108 0]
[ 0 3392 0 0 0 0 0 0 0]
[ 0 738 1862 1 0 4 0 573 0]
[ 0 3148 0 3053 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 6675 0 0 0 4189 0 0 0]
[ 50 0 0 0 0 22 1314 21 0]
[ 142 4684 213 0 0 803 1 2970 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 25481.0
oa: 0.5969404488591107
aa: 0.8536555540070032
kappa: 0.5405504853866452
best accuracy:0.997306
step 86000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000404
step 87000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000400
step 88000, loss_cluster 0.000005 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000005 lr 0.000396
step 89000, loss_cluster 0.000011 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000011 lr 0.000392
step 90000, loss_cluster 0.000016 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000016 lr 0.000387
4998 5000 0.9996
9998 10000 0.9998
14998 15000 0.9998666666666667
19996 20000 0.9998
24995 25000 0.9998
29992 30000 0.9997333333333334
34991 35000 0.9997428571428572
39898 40000 0.99745
42583 42686 0.997587030876634
test end!
1 class: ( 6619.0 / 6621.0 ) 0.9996979308261592
2 class: ( 18636.0 / 18639.0 ) 0.9998390471591824
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3051.0 / 3054.0 ) 0.9990176817288802
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5018.0 / 5019.0 ) 0.9998007571229328
7 class: ( 1319.0 / 1320.0 ) 0.9992424242424243
8 class: ( 3579.0 / 3672.0 ) 0.9746732026143791
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6619 0 0 0 0 0 0 0 0]
[ 0 18636 0 1 0 1 0 0 0]
[ 0 0 2089 0 0 0 0 91 0]
[ 0 0 0 3051 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 3 0 0 0 5018 0 1 0]
[ 2 0 0 0 0 0 1319 1 0]
[ 0 0 0 0 0 0 1 3579 0]
[ 0 0 0 2 0 0 0 0 937]]
total right num: 42583.0
oa: 0.997587030876634
aa: 0.9969190048548842
kappa: 0.9968006772118615
best model saved...
best accuracy:0.997587
step 91000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000383
step 92000, loss_cluster 0.000013 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000013 lr 0.000379
step 93000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000375
step 94000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000371
step 95000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000368
5000 5000 1.0
9998 10000 0.9998
14978 15000 0.9985333333333334
19973 20000 0.99865
24955 25000 0.9982
29953 30000 0.9984333333333333
34953 35000 0.9986571428571429
39877 40000 0.996925
42561 42686 0.9970716394133908
test end!
1 class: ( 6621.0 / 6621.0 ) 1.0
2 class: ( 18592.0 / 18639.0 ) 0.9974784054938569
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1320.0 / 1320.0 ) 1.0
8 class: ( 3594.0 / 3672.0 ) 0.9787581699346405
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6621 0 0 0 0 0 0 0 0]
[ 0 18592 0 0 0 0 0 0 0]
[ 0 0 2089 0 0 0 0 49 0]
[ 0 2 0 3054 0 0 0 0 0]
[ 0 1 0 0 1335 0 0 0 0]
[ 0 38 0 0 0 5019 0 0 0]
[ 0 0 0 0 0 0 1320 29 0]
[ 0 0 0 0 0 0 0 3594 0]
[ 0 6 0 0 0 0 0 0 937]]
total right num: 42561.0
oa: 0.9970716394133908
aa: 0.9973596194920553
kappa: 0.9961191589777799
best accuracy:0.997587
step 96000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000364
step 97000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000360
step 98000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000356
step 99000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000352
step 100000, loss_cluster 0.000464 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000464 lr 0.000349
4994 5000 0.9988
9974 10000 0.9974
14963 15000 0.9975333333333334
19961 20000 0.99805
24961 25000 0.99844
29960 30000 0.9986666666666667
34960 35000 0.9988571428571429
39646 40000 0.99115
42330 42686 0.991660029049337
test end!
1 class: ( 6595.0 / 6621.0 ) 0.9960731007400695
2 class: ( 18625.0 / 18639.0 ) 0.9992488867428511
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1319.0 / 1320.0 ) 0.9992424242424243
8 class: ( 3357.0 / 3672.0 ) 0.9142156862745098
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6595 0 0 0 0 0 0 0 0]
[ 0 18625 0 0 0 0 0 0 0]
[ 0 0 2089 0 0 0 0 240 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 14 0 0 0 5019 0 0 0]
[ 1 0 0 0 0 0 1319 75 0]
[ 25 0 0 0 0 0 1 3357 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 42330.0
oa: 0.991660029049337
aa: 0.9898644553333172
kappa: 0.9889474102123891
best accuracy:0.997587
step 101000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000345
step 102000, loss_cluster 0.000003 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000003 lr 0.000341
step 103000, loss_cluster 0.000017 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000017 lr 0.000338
step 104000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000334
step 105000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000331
5000 5000 1.0
10000 10000 1.0
14990 15000 0.9993333333333333
19984 20000 0.9992
24972 25000 0.99888
29970 30000 0.999
34970 35000 0.9991428571428571
39570 40000 0.98925
42256 42686 0.9899264395820644
test end!
1 class: ( 6621.0 / 6621.0 ) 1.0
2 class: ( 18609.0 / 18639.0 ) 0.9983904715918236
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1319.0 / 1320.0 ) 0.9992424242424243
8 class: ( 3273.0 / 3672.0 ) 0.8913398692810458
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6621 0 0 0 0 0 0 0 0]
[ 0 18609 0 0 0 0 0 0 0]
[ 0 0 2089 0 0 0 0 175 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 1 0 0 1335 0 0 0 0]
[ 0 24 0 0 0 5019 0 0 0]
[ 0 0 0 0 0 0 1319 224 0]
[ 0 0 0 0 0 0 1 3273 0]
[ 0 5 0 0 0 0 0 0 937]]
total right num: 42256.0
oa: 0.9899264395820644
aa: 0.9876636405683661
kappa: 0.9866539468619703
best accuracy:0.997587
step 106000, loss_cluster 0.000010 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000010 lr 0.000327
step 107000, loss_cluster 0.000006 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000006 lr 0.000324
step 108000, loss_cluster 0.000014 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000014 lr 0.000320
step 109000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000317
step 110000, loss_cluster 0.000004 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000004 lr 0.000314
4997 5000 0.9994
9996 10000 0.9996
14979 15000 0.9986
19974 20000 0.9987
24960 25000 0.9984
29959 30000 0.9986333333333334
34959 35000 0.9988285714285714
39675 40000 0.991875
42360 42686 0.9923628355901232
test end!
1 class: ( 6618.0 / 6621.0 ) 0.9995468962392388
2 class: ( 18601.0 / 18639.0 ) 0.9979612640163099
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1319.0 / 1320.0 ) 0.9992424242424243
8 class: ( 3388.0 / 3672.0 ) 0.9226579520697168
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6618 0 0 0 0 0 0 0 0]
[ 0 18601 0 0 0 0 0 0 0]
[ 1 0 2089 0 0 0 0 266 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 29 0 0 0 5019 0 0 0]
[ 2 0 0 0 0 0 1319 18 0]
[ 0 0 0 0 0 0 1 3388 0]
[ 0 9 0 0 0 0 0 0 937]]
total right num: 42360.0
oa: 0.9923628355901232
aa: 0.9910453929519656
kappa: 0.989880330483367
best accuracy:0.997587
step 111000, loss_cluster 0.000005 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000005 lr 0.000311
step 112000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000307
step 113000, loss_cluster 0.000059 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000059 lr 0.000304
step 114000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000301
step 115000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000298
4999 5000 0.9998
9999 10000 0.9999
14998 15000 0.9998666666666667
19998 20000 0.9999
24998 25000 0.99992
29998 30000 0.9999333333333333
34998 35000 0.9999428571428571
39914 40000 0.99785
42596 42686 0.9978915803776414
test end!
1 class: ( 6620.0 / 6621.0 ) 0.9998489654130795
2 class: ( 18638.0 / 18639.0 ) 0.9999463490530608
3 class: ( 2089.0 / 2089.0 ) 1.0
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 5019.0 / 5019.0 ) 1.0
7 class: ( 1318.0 / 1320.0 ) 0.9984848484848485
8 class: ( 3586.0 / 3672.0 ) 0.9765795206971678
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6620 0 0 0 0 0 0 0 0]
[ 0 18638 0 0 0 0 0 0 0]
[ 0 0 2089 0 0 0 0 74 0]
[ 0 0 0 3054 0 0 0 0 0]
[ 0 0 0 0 1335 0 0 0 0]
[ 0 0 0 0 0 5019 0 0 0]
[ 1 0 0 0 0 0 1318 12 0]
[ 0 0 0 0 0 0 2 3586 0]
[ 0 1 0 0 0 0 0 0 937]]
total right num: 42596.0
oa: 0.9978915803776414
aa: 0.9972066315164619
kappa: 0.9972044639802944
best model saved...
best accuracy:0.997892
step 116000, loss_cluster 0.000004 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000004 lr 0.000295
step 117000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000292
step 118000, loss_cluster 0.000002 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000002 lr 0.000288
step 119000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000285
step 120000, loss_cluster 0.000006 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000006 lr 0.000282
4886 5000 0.9772
9666 10000 0.9666
13892 15000 0.9261333333333334
18468 20000 0.9234
22583 25000 0.90332
26021 30000 0.8673666666666666
30342 35000 0.8669142857142857
33641 40000 0.841025
35319 42686 0.8274141404676006
test end!
1 class: ( 6414.0 / 6621.0 ) 0.9687358405074762
2 class: ( 16400.0 / 18639.0 ) 0.879875529803101
3 class: ( 556.0 / 2089.0 ) 0.2661560555289612
4 class: ( 3054.0 / 3054.0 ) 1.0
5 class: ( 1335.0 / 1335.0 ) 1.0
6 class: ( 3941.0 / 5019.0 ) 0.7852161785216178
7 class: ( 1311.0 / 1320.0 ) 0.9931818181818182
8 class: ( 1371.0 / 3672.0 ) 0.37336601307189543
9 class: ( 937.0 / 937.0 ) 1.0
confusion matrix:
[[ 6414 0 0 0 0 0 4 4 0]
[ 10 16400 1019 0 0 1008 0 642 0]
[ 40 0 556 0 0 0 0 35 0]
[ 0 1964 0 3054 0 4 0 0 0]
[ 1 96 123 0 1335 63 0 450 0]
[ 117 179 156 0 0 3941 1 1170 0]
[ 36 0 0 0 0 3 1311 0 0]
[ 3 0 235 0 0 0 4 1371 0]
[ 0 0 0 0 0 0 0 0 937]]
total right num: 35319.0
oa: 0.8274141404676006
aa: 0.8073923817349855
kappa: 0.7701320053783223
best accuracy:0.997892
step 121000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000279
step 122000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000277
step 123000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000274
step 124000, loss_cluster 0.000000 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000000 lr 0.000271
step 125000, loss_cluster 0.000001 ,loss_classification 0.000000,loss_fusion 0.000000,loss_total 0.000001 lr 0.000268
4995 5000 0.999
9993 10000 0.9993
14993 15000 0.9995333333333334
19989 20000 0.99945
24988 25000 0.99952
29984 30000 0.9994666666666666
34984 35000 0.9995428571428572
39827 40000 0.995675
42513 42686 0.9959471489481329
test end!
1 class: ( 6615.0 / 6621.0 ) 0.9990937924784775
2 class: ( 18632.0 / 18639.0 ) 0.9996244433714255
3 class: ( 2086.0 / 2089.0 ) 0.9985639061752034