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)', 840), ('dog(outdoor)', 840), ('cat(outdoor)', 10), ('dog(indoor)', 10)]
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': 0.7696692943572998, 'penalty': 0.17118290066719055}
Iteration: 0
out-of-domain val
accuracy 0.573 	 roc_auc_score 0.655
confusion_matrix
[[ 81 207]
 [ 39 249]]
classification_report
              precision    recall  f1-score   support

           0       0.68      0.28      0.40       288
           1       0.55      0.86      0.67       288

    accuracy                           0.57       576
   macro avg       0.61      0.57      0.53       576
weighted avg       0.61      0.57      0.53       576

VAL * Acc@1 57.292
 * Acc@1 57.292 Acc@5 0.000
accuracy 0.875 	 size: 144 	 dog(indoor)
accuracy 0.854 	 size: 144 	 dog(outdoor)
accuracy 0.361 	 size: 144 	 cat(indoor)
accuracy 0.201 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.6314141750335693, 'penalty': 0.11895568668842316}
step_vals {'loss': 0.5749008655548096, 'penalty': 0.09600821882486343}
step_vals {'loss': 0.491421103477478, 'penalty': 0.07136444747447968}
step_vals {'loss': 0.4024495482444763, 'penalty': 0.05598746985197067}
step_vals {'loss': 0.4664859175682068, 'penalty': 0.05114268511533737}
step_vals {'loss': 0.4290410876274109, 'penalty': 0.052914105355739594}
step_vals {'loss': 0.3596269488334656, 'penalty': 0.056202832609415054}
step_vals {'loss': 0.3112456202507019, 'penalty': 0.04583793133497238}
step_vals {'loss': 0.30595555901527405, 'penalty': 0.04220881685614586}
step_vals {'loss': 0.3143758177757263, 'penalty': 0.04856076464056969}
step_vals {'loss': 0.18268339335918427, 'penalty': 0.05400225892663002}
step_vals {'loss': 0.20218011736869812, 'penalty': 0.06560066342353821}
step_vals {'loss': 0.19861513376235962, 'penalty': 0.05972341448068619}
step_vals {'loss': 0.09985213726758957, 'penalty': 0.06116586923599243}
step_vals {'loss': 0.25656500458717346, 'penalty': 0.05584993213415146}
step_vals {'loss': 0.28752100467681885, 'penalty': 0.09542601555585861}
step_vals {'loss': 0.4660511016845703, 'penalty': 0.1025100126862526}
step_vals {'loss': 0.21437311172485352, 'penalty': 0.07855981588363647}
step_vals {'loss': 0.2738201916217804, 'penalty': 0.06235235184431076}
step_vals {'loss': 0.2341577708721161, 'penalty': 0.0513545423746109}
Iteration: 20
out-of-domain val
accuracy 0.781 	 roc_auc_score 0.869
confusion_matrix
[[216  72]
 [ 54 234]]
classification_report
              precision    recall  f1-score   support

           0       0.80      0.75      0.77       288
           1       0.76      0.81      0.79       288

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

VAL * Acc@1 78.125
 * Acc@1 78.125 Acc@5 0.000
accuracy 0.958 	 size: 144 	 dog(outdoor)
accuracy 0.875 	 size: 144 	 cat(indoor)
accuracy 0.667 	 size: 144 	 dog(indoor)
accuracy 0.625 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.18440726399421692, 'penalty': 0.04138016328215599}
step_vals {'loss': 0.20696225762367249, 'penalty': 0.03198295831680298}
step_vals {'loss': 0.3418828547000885, 'penalty': 0.04017065837979317}
step_vals {'loss': 0.1885068118572235, 'penalty': 0.03782307729125023}
step_vals {'loss': 0.2871226668357849, 'penalty': 0.03767698258161545}
step_vals {'loss': 0.2446003556251526, 'penalty': 0.02362903580069542}
step_vals {'loss': 0.24923190474510193, 'penalty': 0.026117689907550812}
step_vals {'loss': 0.20105914771556854, 'penalty': 0.02126369997859001}
step_vals {'loss': 0.24623584747314453, 'penalty': 0.02495310828089714}
step_vals {'loss': 0.18218471109867096, 'penalty': 0.026575185358524323}
step_vals {'loss': 0.22607016563415527, 'penalty': 0.03725922480225563}
step_vals {'loss': 0.26197096705436707, 'penalty': 0.03284713253378868}
step_vals {'loss': 0.37238603830337524, 'penalty': 0.03258628398180008}
step_vals {'loss': 0.22731290757656097, 'penalty': 0.03018210269510746}
step_vals {'loss': 0.2135496884584427, 'penalty': 0.028116866946220398}
step_vals {'loss': 0.20364755392074585, 'penalty': 0.030025534331798553}
step_vals {'loss': 0.24720458686351776, 'penalty': 0.042434681206941605}
step_vals {'loss': 0.0909682959318161, 'penalty': 0.030207859352231026}
step_vals {'loss': 0.13366326689720154, 'penalty': 0.03372971713542938}
step_vals {'loss': 0.13373643159866333, 'penalty': 0.026383530348539352}
Iteration: 40
out-of-domain val
accuracy 0.776 	 roc_auc_score 0.877
confusion_matrix
[[197  91]
 [ 38 250]]
classification_report
              precision    recall  f1-score   support

           0       0.84      0.68      0.75       288
           1       0.73      0.87      0.79       288

    accuracy                           0.78       576
   macro avg       0.79      0.78      0.77       576
weighted avg       0.79      0.78      0.77       576

VAL * Acc@1 77.604
 * Acc@1 77.604 Acc@5 0.000
accuracy 0.979 	 size: 144 	 dog(outdoor)
accuracy 0.826 	 size: 144 	 cat(indoor)
accuracy 0.757 	 size: 144 	 dog(indoor)
accuracy 0.542 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.28930070996284485, 'penalty': 0.049403443932533264}
step_vals {'loss': 0.09751911461353302, 'penalty': 0.038920965045690536}
step_vals {'loss': 0.19860634207725525, 'penalty': 0.032808177173137665}
step_vals {'loss': 0.22411885857582092, 'penalty': 0.03754834085702896}
step_vals {'loss': 0.17736363410949707, 'penalty': 0.024668261408805847}
step_vals {'loss': 0.1111767366528511, 'penalty': 0.03631940484046936}
step_vals {'loss': 0.21530672907829285, 'penalty': 0.029440894722938538}
step_vals {'loss': 0.3072952628135681, 'penalty': 0.037222400307655334}
step_vals {'loss': 0.18491590023040771, 'penalty': 0.021321898326277733}
step_vals {'loss': 0.11061310768127441, 'penalty': 0.026919996365904808}
step_vals {'loss': 0.1155482828617096, 'penalty': 0.03211814910173416}
step_vals {'loss': 0.13985773921012878, 'penalty': 0.027755986899137497}
step_vals {'loss': 0.23626887798309326, 'penalty': 0.026229048147797585}
step_vals {'loss': 0.17470885813236237, 'penalty': 0.034409187734127045}
step_vals {'loss': 0.17654862999916077, 'penalty': 0.04294559732079506}
step_vals {'loss': 0.10600000619888306, 'penalty': 0.03042953833937645}
step_vals {'loss': 0.18941515684127808, 'penalty': 0.03376540541648865}
step_vals {'loss': 0.10342559218406677, 'penalty': 0.037107400596141815}
step_vals {'loss': 0.04167189449071884, 'penalty': 0.031619057059288025}
step_vals {'loss': 0.141293466091156, 'penalty': 0.034578822553157806}
Iteration: 60
out-of-domain val
accuracy 0.767 	 roc_auc_score 0.863
confusion_matrix
[[217  71]
 [ 63 225]]
classification_report
              precision    recall  f1-score   support

           0       0.78      0.75      0.76       288
           1       0.76      0.78      0.77       288

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

VAL * Acc@1 76.736
 * Acc@1 76.736 Acc@5 0.000
accuracy 0.965 	 size: 144 	 dog(outdoor)
accuracy 0.910 	 size: 144 	 cat(indoor)
accuracy 0.597 	 size: 144 	 cat(outdoor)
accuracy 0.597 	 size: 144 	 dog(indoor)
step_vals {'loss': 0.07380864769220352, 'penalty': 0.04284701123833656}
step_vals {'loss': 0.21399763226509094, 'penalty': 0.06192152574658394}
step_vals {'loss': 0.08938439190387726, 'penalty': 0.03330010175704956}
step_vals {'loss': 0.12812384963035583, 'penalty': 0.0534060038626194}
step_vals {'loss': 0.0697074830532074, 'penalty': 0.036175936460494995}
step_vals {'loss': 0.1410209685564041, 'penalty': 0.027819842100143433}
step_vals {'loss': 0.0610501728951931, 'penalty': 0.04703155905008316}
step_vals {'loss': 0.191180020570755, 'penalty': 0.03329654783010483}
step_vals {'loss': 0.08194759488105774, 'penalty': 0.04602555185556412}
step_vals {'loss': 0.14662721753120422, 'penalty': 0.03945033997297287}
step_vals {'loss': 0.11837597191333771, 'penalty': 0.025095785036683083}
step_vals {'loss': 0.10347548127174377, 'penalty': 0.025888781994581223}
step_vals {'loss': 0.09676597267389297, 'penalty': 0.030107760801911354}
step_vals {'loss': 0.10198131203651428, 'penalty': 0.042890071868896484}
step_vals {'loss': 0.06506186723709106, 'penalty': 0.036307208240032196}
step_vals {'loss': 0.0881500318646431, 'penalty': 0.04761552810668945}
step_vals {'loss': 0.04306771606206894, 'penalty': 0.0322783961892128}
step_vals {'loss': 0.1207563653588295, 'penalty': 0.04529590904712677}
step_vals {'loss': 0.06032061576843262, 'penalty': 0.0315193235874176}
step_vals {'loss': 0.27459290623664856, 'penalty': 0.04605451971292496}
Iteration: 80
out-of-domain val
accuracy 0.755 	 roc_auc_score 0.849
confusion_matrix
[[216  72]
 [ 69 219]]
classification_report
              precision    recall  f1-score   support

           0       0.76      0.75      0.75       288
           1       0.75      0.76      0.76       288

    accuracy                           0.76       576
   macro avg       0.76      0.76      0.76       576
weighted avg       0.76      0.76      0.76       576

VAL * Acc@1 75.521
 * Acc@1 75.521 Acc@5 0.000
accuracy 0.944 	 size: 144 	 dog(outdoor)
accuracy 0.924 	 size: 144 	 cat(indoor)
accuracy 0.576 	 size: 144 	 cat(outdoor)
accuracy 0.576 	 size: 144 	 dog(indoor)
