Meta-causal/code/56720.log

/home/yuqian_fu
{'gpu': '0', 'data': 'cartoon', 'ntr': None, 'translate': None, 'autoaug': 'CA_multiple', 'n': 3, 'stride': 5, 'factor_num': 16, 'epochs': 70, 'nbatch': 100, 'batchsize': 6, 'lr': 0.01, 'lr_scheduler': 'cosine', 'svroot': '/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/saved-PACS//cartoon/CA_multiple_16fa_v2_ep70_lr0.01_cosine_base0.01_bs6_lamCa_1_lamRe1_adt4_cls1_EW2_70_rmTrue_rnTrue_str5_ReProduceMetaCausal', 'clsadapt': True, 'lambda_causal': 1.0, 'lambda_re': 1.0, 'randm': True, 'randn': True, 'network': 'resnet18'}
stride: 5
/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/data/PACS/cartoon_train.hdf5 torch.Size([2107, 3, 227, 227]) torch.Size([2107])
--------------------------CA_multiple--------------------------
---------------------------16 factors-----------------
randm: True
randn: True
n: 3
randm: False
/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/data/PACS/cartoon_val.hdf5 torch.Size([237, 3, 227, 227]) torch.Size([237])
-------------------------------------loading pretrain weights----------------------------------
351
0.01
changing lr
---------------------saving model at epoch 0----------------------------------------------------
epoch 0, time 500.68, cls_loss 5.0126 cls_loss_mapping 1.4019 cls_loss_causal 1.7210 re_mapping 1.0578 re_causal 1.0584 /// teacc 83.12 lr 0.00999497
351
0.009994965332706574
changing lr
---------------------saving model at epoch 1----------------------------------------------------
epoch 1, time 530.56, cls_loss 2.0306 cls_loss_mapping 0.7946 cls_loss_causal 1.3288 re_mapping 0.6527 re_causal 0.6538 /// teacc 87.76 lr 0.00997987
351
0.009979871469976196
changing lr
---------------------saving model at epoch 2----------------------------------------------------
epoch 2, time 536.46, cls_loss 0.6382 cls_loss_mapping 0.4834 cls_loss_causal 1.1278 re_mapping 0.3952 re_causal 0.3957 /// teacc 91.98 lr 0.00995475
351
0.009954748808839675
changing lr
---------------------saving model at epoch 3----------------------------------------------------
epoch 3, time 514.73, cls_loss 0.2115 cls_loss_mapping 0.3043 cls_loss_causal 0.9479 re_mapping 0.2605 re_causal 0.2608 /// teacc 92.41 lr 0.00991965
351
0.009919647942993149
changing lr
epoch 4, time 518.58, cls_loss 0.1048 cls_loss_mapping 0.2504 cls_loss_causal 0.8913 re_mapping 0.2075 re_causal 0.2080 /// teacc 92.41 lr 0.00987464
351
0.009874639560909117
changing lr
---------------------saving model at epoch 5----------------------------------------------------
epoch 5, time 522.88, cls_loss 0.0517 cls_loss_mapping 0.2038 cls_loss_causal 0.8571 re_mapping 0.1746 re_causal 0.1753 /// teacc 95.36 lr 0.00981981
351
0.009819814303479266
changing lr
epoch 6, time 515.51, cls_loss 0.0244 cls_loss_mapping 0.1830 cls_loss_causal 0.7905 re_mapping 0.1502 re_causal 0.1512 /// teacc 94.51 lr 0.00975528
351
0.009755282581475767
changing lr
epoch 7, time 516.68, cls_loss 0.0226 cls_loss_mapping 0.1536 cls_loss_causal 0.7386 re_mapping 0.1335 re_causal 0.1347 /// teacc 94.94 lr 0.00968117
351
0.009681174353198686
changing lr
epoch 8, time 512.83, cls_loss 0.0311 cls_loss_mapping 0.1488 cls_loss_causal 0.7284 re_mapping 0.1200 re_causal 0.1218 /// teacc 91.56 lr 0.00959764
351
0.009597638862757255
changing lr
---------------------saving model at epoch 9----------------------------------------------------
epoch 9, time 515.75, cls_loss 0.0257 cls_loss_mapping 0.1258 cls_loss_causal 0.7038 re_mapping 0.1090 re_causal 0.1110 /// teacc 95.78 lr 0.00950484
351
0.009504844339512096
changing lr
epoch 10, time 508.97, cls_loss 0.0086 cls_loss_mapping 0.1049 cls_loss_causal 0.7078 re_mapping 0.0973 re_causal 0.0997 /// teacc 94.09 lr 0.00940298
351
0.009402977659283692
changing lr
epoch 11, time 522.72, cls_loss 0.0121 cls_loss_mapping 0.1017 cls_loss_causal 0.6880 re_mapping 0.0899 re_causal 0.0929 /// teacc 95.36 lr 0.00929224
351
0.009292243968009333
changing lr
epoch 12, time 511.13, cls_loss 0.0138 cls_loss_mapping 0.0946 cls_loss_causal 0.7011 re_mapping 0.0820 re_causal 0.0855 /// teacc 94.94 lr 0.00917287
351
0.009172866268606516
changing lr
epoch 13, time 522.62, cls_loss 0.0104 cls_loss_mapping 0.0844 cls_loss_causal 0.6675 re_mapping 0.0747 re_causal 0.0784 /// teacc 94.51 lr 0.00904508
351
0.00904508497187474
changing lr
epoch 14, time 530.18, cls_loss 0.0122 cls_loss_mapping 0.0736 cls_loss_causal 0.6363 re_mapping 0.0698 re_causal 0.0745 /// teacc 95.78 lr 0.00890916
351
0.008909157412340152
changing lr
epoch 15, time 513.03, cls_loss 0.0108 cls_loss_mapping 0.0735 cls_loss_causal 0.6055 re_mapping 0.0623 re_causal 0.0673 /// teacc 94.94 lr 0.00876536
351
0.00876535733001806
changing lr
---------------------saving model at epoch 16----------------------------------------------------
epoch 16, time 515.62, cls_loss 0.0097 cls_loss_mapping 0.0626 cls_loss_causal 0.6328 re_mapping 0.0572 re_causal 0.0629 /// teacc 97.05 lr 0.00861397
351
0.008613974319136962
changing lr
epoch 17, time 534.26, cls_loss 0.0145 cls_loss_mapping 0.0706 cls_loss_causal 0.6484 re_mapping 0.0533 re_causal 0.0603 /// teacc 96.20 lr 0.00845531
351
0.008455313244934327
changing lr
epoch 18, time 532.03, cls_loss 0.0106 cls_loss_mapping 0.0571 cls_loss_causal 0.5705 re_mapping 0.0492 re_causal 0.0567 /// teacc 96.62 lr 0.00828969
351
0.008289693629698565
changing lr
epoch 19, time 518.07, cls_loss 0.0076 cls_loss_mapping 0.0474 cls_loss_causal 0.5525 re_mapping 0.0441 re_causal 0.0513 /// teacc 95.78 lr 0.00811745
351
0.00811744900929367
changing lr
epoch 20, time 530.26, cls_loss 0.0081 cls_loss_mapping 0.0546 cls_loss_causal 0.5926 re_mapping 0.0409 re_causal 0.0491 /// teacc 97.05 lr 0.00793893
351
0.007938926261462368
changing lr
epoch 21, time 534.00, cls_loss 0.0104 cls_loss_mapping 0.0511 cls_loss_causal 0.5469 re_mapping 0.0373 re_causal 0.0451 /// teacc 95.78 lr 0.00775448
351
0.007754484907260515
changing lr
epoch 22, time 534.87, cls_loss 0.0148 cls_loss_mapping 0.0474 cls_loss_causal 0.5694 re_mapping 0.0353 re_causal 0.0430 /// teacc 95.36 lr 0.00756450
351
0.007564496387029534
changing lr
epoch 23, time 515.04, cls_loss 0.0053 cls_loss_mapping 0.0395 cls_loss_causal 0.5557 re_mapping 0.0324 re_causal 0.0409 /// teacc 96.62 lr 0.00736934
351
0.007369343312364995
changing lr
epoch 24, time 527.73, cls_loss 0.0083 cls_loss_mapping 0.0487 cls_loss_causal 0.5594 re_mapping 0.0306 re_causal 0.0402 /// teacc 94.94 lr 0.00716942
351
0.0071694186955877925
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epoch 25, time 521.10, cls_loss 0.0080 cls_loss_mapping 0.0392 cls_loss_causal 0.5600 re_mapping 0.0291 re_causal 0.0390 /// teacc 97.05 lr 0.00696513
351
0.0069651251582696205
changing lr
epoch 26, time 528.30, cls_loss 0.0054 cls_loss_mapping 0.0316 cls_loss_causal 0.5380 re_mapping 0.0270 re_causal 0.0366 /// teacc 96.20 lr 0.00675687
351
0.006756874120406716
changing lr
epoch 27, time 526.16, cls_loss 0.0075 cls_loss_mapping 0.0354 cls_loss_causal 0.5384 re_mapping 0.0251 re_causal 0.0347 /// teacc 97.05 lr 0.00654508
351
0.00654508497187474
changing lr
epoch 28, time 520.46, cls_loss 0.0066 cls_loss_mapping 0.0281 cls_loss_causal 0.5043 re_mapping 0.0240 re_causal 0.0354 /// teacc 96.62 lr 0.00633018
351
0.006330184227833378
changing lr
epoch 29, time 536.80, cls_loss 0.0074 cls_loss_mapping 0.0305 cls_loss_causal 0.5296 re_mapping 0.0227 re_causal 0.0341 /// teacc 95.78 lr 0.00611260
351
0.006112604669781575
changing lr
epoch 30, time 530.96, cls_loss 0.0062 cls_loss_mapping 0.0301 cls_loss_causal 0.5251 re_mapping 0.0214 re_causal 0.0317 /// teacc 96.20 lr 0.00589278
351
0.005892784473993186
changing lr
epoch 31, time 528.74, cls_loss 0.0051 cls_loss_mapping 0.0263 cls_loss_causal 0.5350 re_mapping 0.0205 re_causal 0.0317 /// teacc 96.20 lr 0.00567117
351
0.00567116632908828
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---------------------saving model at epoch 32----------------------------------------------------
epoch 32, time 517.42, cls_loss 0.0051 cls_loss_mapping 0.0225 cls_loss_causal 0.5060 re_mapping 0.0197 re_causal 0.0305 /// teacc 97.47 lr 0.00544820
351
0.00544819654451717
changing lr
---------------------saving model at epoch 33----------------------------------------------------
epoch 33, time 532.29, cls_loss 0.0050 cls_loss_mapping 0.0196 cls_loss_causal 0.5099 re_mapping 0.0185 re_causal 0.0291 /// teacc 97.89 lr 0.00522432
351
0.005224324151752577
changing lr
epoch 34, time 521.23, cls_loss 0.0079 cls_loss_mapping 0.0235 cls_loss_causal 0.5058 re_mapping 0.0177 re_causal 0.0285 /// teacc 97.89 lr 0.00500000
351
0.005000000000000003
changing lr
epoch 35, time 521.42, cls_loss 0.0054 cls_loss_mapping 0.0236 cls_loss_causal 0.4683 re_mapping 0.0178 re_causal 0.0281 /// teacc 97.05 lr 0.00477568
351
0.004775675848247429
changing lr
epoch 36, time 526.29, cls_loss 0.0057 cls_loss_mapping 0.0231 cls_loss_causal 0.5159 re_mapping 0.0172 re_causal 0.0278 /// teacc 97.05 lr 0.00455180
351
0.004551803455482836
changing lr
epoch 37, time 535.59, cls_loss 0.0063 cls_loss_mapping 0.0199 cls_loss_causal 0.4658 re_mapping 0.0163 re_causal 0.0267 /// teacc 97.47 lr 0.00432883
351
0.004328833670911726
changing lr
epoch 38, time 512.58, cls_loss 0.0045 cls_loss_mapping 0.0199 cls_loss_causal 0.4925 re_mapping 0.0155 re_causal 0.0258 /// teacc 97.05 lr 0.00410722
351
0.0041072155260068206
changing lr
epoch 39, time 532.69, cls_loss 0.0056 cls_loss_mapping 0.0220 cls_loss_causal 0.4772 re_mapping 0.0150 re_causal 0.0253 /// teacc 97.47 lr 0.00388740
351
0.0038873953302184317
changing lr
epoch 40, time 536.18, cls_loss 0.0044 cls_loss_mapping 0.0185 cls_loss_causal 0.4992 re_mapping 0.0146 re_causal 0.0241 /// teacc 97.47 lr 0.00366982
351
0.003669815772166629
changing lr
epoch 41, time 531.87, cls_loss 0.0044 cls_loss_mapping 0.0147 cls_loss_causal 0.4840 re_mapping 0.0144 re_causal 0.0246 /// teacc 97.89 lr 0.00345492
351
0.0034549150281252667
changing lr
---------------------saving model at epoch 42----------------------------------------------------
epoch 42, time 509.65, cls_loss 0.0045 cls_loss_mapping 0.0164 cls_loss_causal 0.4600 re_mapping 0.0136 re_causal 0.0224 /// teacc 98.31 lr 0.00324313
351
0.0032431258795932905
changing lr
epoch 43, time 520.56, cls_loss 0.0051 cls_loss_mapping 0.0169 cls_loss_causal 0.5021 re_mapping 0.0137 re_causal 0.0235 /// teacc 97.47 lr 0.00303487
351
0.0030348748417303863
changing lr
---------------------saving model at epoch 44----------------------------------------------------
epoch 44, time 532.35, cls_loss 0.0042 cls_loss_mapping 0.0153 cls_loss_causal 0.4512 re_mapping 0.0131 re_causal 0.0230 /// teacc 98.73 lr 0.00283058
351
0.0028305813044122124
changing lr
epoch 45, time 523.83, cls_loss 0.0053 cls_loss_mapping 0.0159 cls_loss_causal 0.4523 re_mapping 0.0130 re_causal 0.0219 /// teacc 97.89 lr 0.00263066
351
0.0026306566876350096
changing lr
epoch 46, time 536.05, cls_loss 0.0050 cls_loss_mapping 0.0148 cls_loss_causal 0.4521 re_mapping 0.0125 re_causal 0.0215 /// teacc 96.62 lr 0.00243550
351
0.0024355036129704724
changing lr
epoch 47, time 509.13, cls_loss 0.0043 cls_loss_mapping 0.0159 cls_loss_causal 0.4864 re_mapping 0.0121 re_causal 0.0214 /// teacc 97.89 lr 0.00224552
351
0.00224551509273949
changing lr
epoch 48, time 524.58, cls_loss 0.0037 cls_loss_mapping 0.0109 cls_loss_causal 0.4474 re_mapping 0.0120 re_causal 0.0208 /// teacc 98.31 lr 0.00206107
351
0.002061073738537637
changing lr
epoch 49, time 517.27, cls_loss 0.0033 cls_loss_mapping 0.0125 cls_loss_causal 0.4527 re_mapping 0.0117 re_causal 0.0205 /// teacc 97.89 lr 0.00188255
351
0.0018825509907063344
changing lr
epoch 50, time 516.76, cls_loss 0.0039 cls_loss_mapping 0.0142 cls_loss_causal 0.4602 re_mapping 0.0116 re_causal 0.0204 /// teacc 97.47 lr 0.00171031
351
0.0017103063703014388
changing lr
epoch 51, time 513.81, cls_loss 0.0025 cls_loss_mapping 0.0098 cls_loss_causal 0.4081 re_mapping 0.0116 re_causal 0.0197 /// teacc 98.31 lr 0.00154469
351
0.0015446867550656784
changing lr
epoch 52, time 514.01, cls_loss 0.0042 cls_loss_mapping 0.0125 cls_loss_causal 0.4603 re_mapping 0.0114 re_causal 0.0195 /// teacc 97.89 lr 0.00138603
351
0.001386025680863044
changing lr
epoch 53, time 524.35, cls_loss 0.0051 cls_loss_mapping 0.0127 cls_loss_causal 0.4572 re_mapping 0.0111 re_causal 0.0193 /// teacc 97.89 lr 0.00123464
351
0.0012346426699819469
changing lr
epoch 54, time 514.44, cls_loss 0.0044 cls_loss_mapping 0.0127 cls_loss_causal 0.4353 re_mapping 0.0111 re_causal 0.0187 /// teacc 97.47 lr 0.00109084
351
0.0010908425876598518
changing lr
epoch 55, time 522.77, cls_loss 0.0037 cls_loss_mapping 0.0112 cls_loss_causal 0.4375 re_mapping 0.0109 re_causal 0.0188 /// teacc 98.31 lr 0.00095492
351
0.000954915028125264
changing lr
epoch 56, time 523.02, cls_loss 0.0041 cls_loss_mapping 0.0109 cls_loss_causal 0.4403 re_mapping 0.0108 re_causal 0.0186 /// teacc 97.05 lr 0.00082713
351
0.0008271337313934874
changing lr
epoch 57, time 527.11, cls_loss 0.0028 cls_loss_mapping 0.0091 cls_loss_causal 0.4157 re_mapping 0.0108 re_causal 0.0176 /// teacc 97.47 lr 0.00070776
351
0.00070775603199067
changing lr
epoch 58, time 504.49, cls_loss 0.0031 cls_loss_mapping 0.0086 cls_loss_causal 0.4095 re_mapping 0.0108 re_causal 0.0171 /// teacc 97.89 lr 0.00059702
351
0.0005970223407163104
changing lr
epoch 59, time 497.53, cls_loss 0.0053 cls_loss_mapping 0.0115 cls_loss_causal 0.4429 re_mapping 0.0105 re_causal 0.0172 /// teacc 97.05 lr 0.00049516
351
0.0004951556604879052
changing lr
epoch 60, time 507.85, cls_loss 0.0043 cls_loss_mapping 0.0108 cls_loss_causal 0.4240 re_mapping 0.0103 re_causal 0.0166 /// teacc 98.31 lr 0.00040236
351
0.00040236113724274745
changing lr
epoch 61, time 489.10, cls_loss 0.0040 cls_loss_mapping 0.0104 cls_loss_causal 0.4613 re_mapping 0.0103 re_causal 0.0175 /// teacc 97.05 lr 0.00031883
351
0.00031882564680131423
changing lr
epoch 62, time 487.44, cls_loss 0.0040 cls_loss_mapping 0.0101 cls_loss_causal 0.4445 re_mapping 0.0102 re_causal 0.0167 /// teacc 98.31 lr 0.00024472
351
0.0002447174185242325
changing lr
epoch 63, time 492.60, cls_loss 0.0030 cls_loss_mapping 0.0067 cls_loss_causal 0.3786 re_mapping 0.0102 re_causal 0.0165 /// teacc 97.89 lr 0.00018019
351
0.0001801856965207339
changing lr
epoch 64, time 493.59, cls_loss 0.0040 cls_loss_mapping 0.0106 cls_loss_causal 0.4459 re_mapping 0.0101 re_causal 0.0165 /// teacc 96.62 lr 0.00012536
351
0.000125360439090882
changing lr
epoch 65, time 485.22, cls_loss 0.0051 cls_loss_mapping 0.0094 cls_loss_causal 0.4355 re_mapping 0.0101 re_causal 0.0162 /// teacc 97.47 lr 0.00008035
351
8.03520570068517e-05
changing lr
epoch 66, time 475.77, cls_loss 0.0036 cls_loss_mapping 0.0086 cls_loss_causal 0.4274 re_mapping 0.0101 re_causal 0.0165 /// teacc 97.89 lr 0.00004525
351
4.5251191160326525e-05
changing lr
epoch 67, time 483.43, cls_loss 0.0043 cls_loss_mapping 0.0107 cls_loss_causal 0.4531 re_mapping 0.0102 re_causal 0.0168 /// teacc 96.62 lr 0.00002013
351
2.0128530023804673e-05
changing lr
epoch 68, time 484.93, cls_loss 0.0030 cls_loss_mapping 0.0073 cls_loss_causal 0.4376 re_mapping 0.0102 re_causal 0.0166 /// teacc 97.89 lr 0.00000503
351
5.034667293427056e-06
changing lr
epoch 69, time 479.93, cls_loss 0.0041 cls_loss_mapping 0.0089 cls_loss_causal 0.4412 re_mapping 0.0100 re_causal 0.0165 /// teacc 96.20 lr 0.00000000
---------------------saving last model at epoch 69----------------------------------------------------
/home/yuqian_fu
{'gpu': '0', 'svroot': '/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/saved-PACS//cartoon/CA_multiple_16fa_v2_ep70_lr0.01_cosine_base0.01_bs6_lamCa_1_lamRe1_adt4_cls1_EW2_70_rmTrue_rnTrue_str5_ReProduceMetaCausal', 'source_domain': 'cartoon', 'svpath': '/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/saved-PACS//cartoon/CA_multiple_16fa_v2_ep70_lr0.01_cosine_base0.01_bs6_lamCa_1_lamRe1_adt4_cls1_EW2_70_rmTrue_rnTrue_str5_ReProduceMetaCausal/cartoon_16factor_last_test_check.csv', 'factor_num': 16, 'epoch': 'last', 'stride': 5, 'eval_mapping': False, 'network': 'resnet18'}
-------------------------------------loading pretrain weights----------------------------------
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randm: False
stride: 5
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columns: ['cartoon', 'art_painting', 'photo', 'sketch']
/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/data/PACS/cartoon_test.hdf5 torch.Size([2344, 3, 227, 227]) torch.Size([2344])
/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/data/PACS/art_painting_test.hdf5 torch.Size([2048, 3, 227, 227]) torch.Size([2048])
/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/data/PACS/photo_test.hdf5 torch.Size([1670, 3, 227, 227]) torch.Size([1670])
/data/work-gcp-europe-west4-a/yuqian_fu/datasets/SingleSourceDG/data/PACS/sketch_test.hdf5 torch.Size([3929, 3, 227, 227]) torch.Size([3929])
                       cartoon  art_painting      photo     sketch        Avg
w/o do (original x)  99.616041     76.806641  89.700599  72.613897  79.707045
      cartoon  art_painting      photo     sketch        Avg
do  99.573379     75.537109  89.760479  73.631967  79.643185