Environment:
	Python: 3.6.13
	PyTorch: 1.4.0
	Torchvision: 0.5.0
	CUDA: 10.1
	CUDNN: 7603
	NumPy: 1.19.5
	PIL: 8.1.0
Args:
	algorithm: CORAL
	batch_size: 8
	data: /data/GQA/MetaDataset-subpopulation-shift
	hparams: None
	hparams_seed: 0
	log_prefix: 
	num_classes: 2
	num_domains: 2
	output_dir: train_output
	save_model_every_checkpoint: False
	seed: 0
	skip_model_save: False
	workers: 4
train_dataset.samples reverse: [('cat(indoor)', 800), ('dog(outdoor)', 800), ('cat(outdoor)', 50), ('dog(indoor)', 50)]
self.domain_to_groups {0: {'cat': ['cat(indoor)'], 'dog': ['dog(indoor)']}, 1: {'cat': ['cat(outdoor)'], 'dog': ['dog(outdoor)']}}
HParams:
	batch_size: 32
	class_balanced: False
	data_augmentation: True
	lr: 5e-05
	mmd_gamma: 1.0
	nonlinear_classifier: False
	resnet18: True
	resnet_dropout: 0.0
	weight_decay: 0.0
step_vals {'loss': 0.704740583896637, 'penalty': 0.20237234234809875}
Iteration: 0
out-of-domain val
accuracy 0.566 	 roc_auc_score 0.608
confusion_matrix
[[131 157]
 [ 93 195]]
classification_report
              precision    recall  f1-score   support

           0       0.58      0.45      0.51       288
           1       0.55      0.68      0.61       288

    accuracy                           0.57       576
   macro avg       0.57      0.57      0.56       576
weighted avg       0.57      0.57      0.56       576

VAL * Acc@1 56.597
 * Acc@1 56.597 Acc@5 0.000
accuracy 0.688 	 size: 144 	 dog(indoor)
accuracy 0.667 	 size: 144 	 dog(outdoor)
accuracy 0.507 	 size: 144 	 cat(indoor)
accuracy 0.403 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.7258767485618591, 'penalty': 0.13456951081752777}
step_vals {'loss': 0.6746721267700195, 'penalty': 0.09887377172708511}
step_vals {'loss': 0.5933246612548828, 'penalty': 0.08552316576242447}
step_vals {'loss': 0.6526457071304321, 'penalty': 0.06928885728120804}
step_vals {'loss': 0.5910747051239014, 'penalty': 0.06201714649796486}
step_vals {'loss': 0.5799403190612793, 'penalty': 0.04026411473751068}
step_vals {'loss': 0.49700891971588135, 'penalty': 0.028412997722625732}
step_vals {'loss': 0.4770893156528473, 'penalty': 0.039391010999679565}
step_vals {'loss': 0.571716845035553, 'penalty': 0.029279081150889397}
step_vals {'loss': 0.4701007008552551, 'penalty': 0.03545565903186798}
step_vals {'loss': 0.5574329495429993, 'penalty': 0.027640450745821}
step_vals {'loss': 0.4735519289970398, 'penalty': 0.027408091351389885}
step_vals {'loss': 0.4466189742088318, 'penalty': 0.026858322322368622}
step_vals {'loss': 0.5081107020378113, 'penalty': 0.03614499419927597}
step_vals {'loss': 0.4915655553340912, 'penalty': 0.02818995714187622}
step_vals {'loss': 0.5023664236068726, 'penalty': 0.043041616678237915}
step_vals {'loss': 0.4001481235027313, 'penalty': 0.04381055384874344}
step_vals {'loss': 0.32953912019729614, 'penalty': 0.04208076372742653}
step_vals {'loss': 0.34727948904037476, 'penalty': 0.03452739864587784}
step_vals {'loss': 0.40795430541038513, 'penalty': 0.04548271745443344}
Iteration: 20
out-of-domain val
accuracy 0.769 	 roc_auc_score 0.870
confusion_matrix
[[248  40]
 [ 93 195]]
classification_report
              precision    recall  f1-score   support

           0       0.73      0.86      0.79       288
           1       0.83      0.68      0.75       288

    accuracy                           0.77       576
   macro avg       0.78      0.77      0.77       576
weighted avg       0.78      0.77      0.77       576

VAL * Acc@1 76.910
 * Acc@1 76.910 Acc@5 0.000
accuracy 0.931 	 size: 144 	 cat(indoor)
accuracy 0.792 	 size: 144 	 cat(outdoor)
accuracy 0.764 	 size: 144 	 dog(outdoor)
accuracy 0.590 	 size: 144 	 dog(indoor)
step_vals {'loss': 0.3409804105758667, 'penalty': 0.04355049878358841}
step_vals {'loss': 0.5437129735946655, 'penalty': 0.09850207716226578}
step_vals {'loss': 0.4363994598388672, 'penalty': 0.04219265654683113}
step_vals {'loss': 0.33118489384651184, 'penalty': 0.05072779580950737}
step_vals {'loss': 0.4173377454280853, 'penalty': 0.04265004023909569}
step_vals {'loss': 0.3316388428211212, 'penalty': 0.04333021864295006}
step_vals {'loss': 0.41408777236938477, 'penalty': 0.07153113186359406}
step_vals {'loss': 0.3303182125091553, 'penalty': 0.05871666222810745}
step_vals {'loss': 0.38174325227737427, 'penalty': 0.03298226743936539}
step_vals {'loss': 0.29585060477256775, 'penalty': 0.03033711388707161}
step_vals {'loss': 0.35865187644958496, 'penalty': 0.03271209076046944}
step_vals {'loss': 0.318010151386261, 'penalty': 0.03331025689840317}
step_vals {'loss': 0.4107494056224823, 'penalty': 0.0425524041056633}
step_vals {'loss': 0.2876739799976349, 'penalty': 0.043276574462652206}
step_vals {'loss': 0.26369428634643555, 'penalty': 0.0335245281457901}
step_vals {'loss': 0.23026204109191895, 'penalty': 0.029793158173561096}
step_vals {'loss': 0.37557166814804077, 'penalty': 0.03943484276533127}
step_vals {'loss': 0.31357795000076294, 'penalty': 0.032707471400499344}
step_vals {'loss': 0.3065173923969269, 'penalty': 0.05029476433992386}
step_vals {'loss': 0.38307955861091614, 'penalty': 0.07065066695213318}
Iteration: 40
out-of-domain val
accuracy 0.823 	 roc_auc_score 0.896
confusion_matrix
[[237  51]
 [ 51 237]]
classification_report
              precision    recall  f1-score   support

           0       0.82      0.82      0.82       288
           1       0.82      0.82      0.82       288

    accuracy                           0.82       576
   macro avg       0.82      0.82      0.82       576
weighted avg       0.82      0.82      0.82       576

VAL * Acc@1 82.292
 * Acc@1 82.292 Acc@5 0.000
accuracy 0.938 	 size: 144 	 dog(outdoor)
accuracy 0.917 	 size: 144 	 cat(indoor)
accuracy 0.729 	 size: 144 	 cat(outdoor)
accuracy 0.708 	 size: 144 	 dog(indoor)
step_vals {'loss': 0.34583592414855957, 'penalty': 0.041168179363012314}
step_vals {'loss': 0.2890854775905609, 'penalty': 0.04965759813785553}
step_vals {'loss': 0.2589130401611328, 'penalty': 0.04052738472819328}
step_vals {'loss': 0.3113577365875244, 'penalty': 0.030435966327786446}
step_vals {'loss': 0.18130677938461304, 'penalty': 0.03259003907442093}
step_vals {'loss': 0.3814936876296997, 'penalty': 0.0492798276245594}
step_vals {'loss': 0.2284964919090271, 'penalty': 0.03654313087463379}
step_vals {'loss': 0.35561567544937134, 'penalty': 0.044976554811000824}
step_vals {'loss': 0.17349833250045776, 'penalty': 0.04648676514625549}
step_vals {'loss': 0.3011859655380249, 'penalty': 0.04084791988134384}
step_vals {'loss': 0.4241783916950226, 'penalty': 0.047332026064395905}
step_vals {'loss': 0.4778614938259125, 'penalty': 0.03274345397949219}
step_vals {'loss': 0.35414791107177734, 'penalty': 0.03164515271782875}
step_vals {'loss': 0.3996618390083313, 'penalty': 0.04699423536658287}
step_vals {'loss': 0.2487044632434845, 'penalty': 0.04133889079093933}
step_vals {'loss': 0.3627537190914154, 'penalty': 0.0270451158285141}
step_vals {'loss': 0.3007802963256836, 'penalty': 0.02565908245742321}
step_vals {'loss': 0.24458757042884827, 'penalty': 0.01988367736339569}
step_vals {'loss': 0.24886323511600494, 'penalty': 0.02403479442000389}
step_vals {'loss': 0.28209471702575684, 'penalty': 0.035579241812229156}
Iteration: 60
out-of-domain val
accuracy 0.793 	 roc_auc_score 0.893
confusion_matrix
[[246  42]
 [ 77 211]]
classification_report
              precision    recall  f1-score   support

           0       0.76      0.85      0.81       288
           1       0.83      0.73      0.78       288

    accuracy                           0.79       576
   macro avg       0.80      0.79      0.79       576
weighted avg       0.80      0.79      0.79       576

VAL * Acc@1 79.340
 * Acc@1 79.340 Acc@5 0.000
accuracy 0.931 	 size: 144 	 cat(indoor)
accuracy 0.854 	 size: 144 	 dog(outdoor)
accuracy 0.778 	 size: 144 	 cat(outdoor)
accuracy 0.611 	 size: 144 	 dog(indoor)
step_vals {'loss': 0.26629912853240967, 'penalty': 0.024256806820631027}
step_vals {'loss': 0.32106825709342957, 'penalty': 0.02364862710237503}
step_vals {'loss': 0.23428118228912354, 'penalty': 0.024285584688186646}
step_vals {'loss': 0.11698015034198761, 'penalty': 0.03383185714483261}
step_vals {'loss': 0.37872111797332764, 'penalty': 0.024831736460328102}
step_vals {'loss': 0.27194350957870483, 'penalty': 0.04197702556848526}
step_vals {'loss': 0.21616056561470032, 'penalty': 0.03788026422262192}
step_vals {'loss': 0.24723690748214722, 'penalty': 0.03203931823372841}
step_vals {'loss': 0.22101905941963196, 'penalty': 0.026379628106951714}
step_vals {'loss': 0.17846280336380005, 'penalty': 0.021672720089554787}
step_vals {'loss': 0.17381061613559723, 'penalty': 0.05882192403078079}
step_vals {'loss': 0.2974681556224823, 'penalty': 0.036000095307826996}
step_vals {'loss': 0.4070481061935425, 'penalty': 0.05527127534151077}
step_vals {'loss': 0.1716325283050537, 'penalty': 0.03168804943561554}
step_vals {'loss': 0.22465433180332184, 'penalty': 0.04285382479429245}
step_vals {'loss': 0.21074432134628296, 'penalty': 0.026744721457362175}
step_vals {'loss': 0.2556161880493164, 'penalty': 0.03240209445357323}
step_vals {'loss': 0.2700226902961731, 'penalty': 0.06785199046134949}
step_vals {'loss': 0.24663984775543213, 'penalty': 0.037591300904750824}
step_vals {'loss': 0.2509635090827942, 'penalty': 0.03473368287086487}
Iteration: 80
out-of-domain val
accuracy 0.816 	 roc_auc_score 0.891
confusion_matrix
[[236  52]
 [ 54 234]]
classification_report
              precision    recall  f1-score   support

           0       0.81      0.82      0.82       288
           1       0.82      0.81      0.82       288

    accuracy                           0.82       576
   macro avg       0.82      0.82      0.82       576
weighted avg       0.82      0.82      0.82       576

VAL * Acc@1 81.597
 * Acc@1 81.597 Acc@5 0.000
accuracy 0.931 	 size: 144 	 dog(outdoor)
accuracy 0.924 	 size: 144 	 cat(indoor)
accuracy 0.715 	 size: 144 	 cat(outdoor)
accuracy 0.694 	 size: 144 	 dog(indoor)
