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)', 750), ('dog(outdoor)', 750), ('cat(outdoor)', 100), ('dog(indoor)', 100)]
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': 0.7828301191329956, 'penalty': 0.1997123658657074}
Iteration: 0
out-of-domain val
accuracy 0.568 	 roc_auc_score 0.660
confusion_matrix
[[ 65 223]
 [ 26 262]]
classification_report
              precision    recall  f1-score   support

           0       0.71      0.23      0.34       288
           1       0.54      0.91      0.68       288

    accuracy                           0.57       576
   macro avg       0.63      0.57      0.51       576
weighted avg       0.63      0.57      0.51       576

VAL * Acc@1 56.771
 * Acc@1 56.771 Acc@5 0.000
accuracy 0.910 	 size: 144 	 dog(indoor)
accuracy 0.910 	 size: 144 	 dog(outdoor)
accuracy 0.278 	 size: 144 	 cat(indoor)
accuracy 0.174 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.6904791593551636, 'penalty': 0.14076003432273865}
step_vals {'loss': 0.685199499130249, 'penalty': 0.09280048310756683}
step_vals {'loss': 0.51093590259552, 'penalty': 0.06533360481262207}
step_vals {'loss': 0.5897910594940186, 'penalty': 0.0758502185344696}
step_vals {'loss': 0.5132601857185364, 'penalty': 0.0572238564491272}
step_vals {'loss': 0.5252109169960022, 'penalty': 0.04219753295183182}
step_vals {'loss': 0.5569320917129517, 'penalty': 0.04393910616636276}
step_vals {'loss': 0.5402631759643555, 'penalty': 0.035989195108413696}
step_vals {'loss': 0.531242847442627, 'penalty': 0.03534870594739914}
step_vals {'loss': 0.5576534271240234, 'penalty': 0.03288324922323227}
step_vals {'loss': 0.42437535524368286, 'penalty': 0.025485292077064514}
step_vals {'loss': 0.48885852098464966, 'penalty': 0.029206182807683945}
step_vals {'loss': 0.4576737582683563, 'penalty': 0.054423898458480835}
step_vals {'loss': 0.36882317066192627, 'penalty': 0.03960074111819267}
step_vals {'loss': 0.45444560050964355, 'penalty': 0.038595810532569885}
step_vals {'loss': 0.5608977675437927, 'penalty': 0.03292124718427658}
step_vals {'loss': 0.49795466661453247, 'penalty': 0.03799113258719444}
step_vals {'loss': 0.3602127730846405, 'penalty': 0.043372105807065964}
step_vals {'loss': 0.5194007754325867, 'penalty': 0.04081112518906593}
step_vals {'loss': 0.37488508224487305, 'penalty': 0.035502538084983826}
Iteration: 20
out-of-domain val
accuracy 0.766 	 roc_auc_score 0.889
confusion_matrix
[[171 117]
 [ 18 270]]
classification_report
              precision    recall  f1-score   support

           0       0.90      0.59      0.72       288
           1       0.70      0.94      0.80       288

    accuracy                           0.77       576
   macro avg       0.80      0.77      0.76       576
weighted avg       0.80      0.77      0.76       576

VAL * Acc@1 76.562
 * Acc@1 76.562 Acc@5 0.000
accuracy 0.986 	 size: 144 	 dog(outdoor)
accuracy 0.889 	 size: 144 	 dog(indoor)
accuracy 0.653 	 size: 144 	 cat(indoor)
accuracy 0.535 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.2829321622848511, 'penalty': 0.043544039130210876}
step_vals {'loss': 0.4140254259109497, 'penalty': 0.04512474685907364}
step_vals {'loss': 0.5018842816352844, 'penalty': 0.04183356463909149}
step_vals {'loss': 0.437378466129303, 'penalty': 0.04687216877937317}
step_vals {'loss': 0.35274386405944824, 'penalty': 0.035023871809244156}
step_vals {'loss': 0.5147804021835327, 'penalty': 0.03797616809606552}
step_vals {'loss': 0.36751559376716614, 'penalty': 0.05539839342236519}
step_vals {'loss': 0.35710251331329346, 'penalty': 0.027229759842157364}
step_vals {'loss': 0.3090400695800781, 'penalty': 0.049918390810489655}
step_vals {'loss': 0.500409722328186, 'penalty': 0.07477714121341705}
step_vals {'loss': 0.28562790155410767, 'penalty': 0.03503946587443352}
step_vals {'loss': 0.3915892243385315, 'penalty': 0.052223432809114456}
step_vals {'loss': 0.49885356426239014, 'penalty': 0.037188224494457245}
step_vals {'loss': 0.3330232501029968, 'penalty': 0.030940361320972443}
step_vals {'loss': 0.42401960492134094, 'penalty': 0.045373983681201935}
step_vals {'loss': 0.3403298854827881, 'penalty': 0.034263838082551956}
step_vals {'loss': 0.30390286445617676, 'penalty': 0.028016332536935806}
step_vals {'loss': 0.44245246052742004, 'penalty': 0.026538986712694168}
step_vals {'loss': 0.47617700695991516, 'penalty': 0.025073431432247162}
step_vals {'loss': 0.4390442371368408, 'penalty': 0.028809070587158203}
Iteration: 40
out-of-domain val
accuracy 0.825 	 roc_auc_score 0.915
confusion_matrix
[[218  70]
 [ 31 257]]
classification_report
              precision    recall  f1-score   support

           0       0.88      0.76      0.81       288
           1       0.79      0.89      0.84       288

    accuracy                           0.82       576
   macro avg       0.83      0.82      0.82       576
weighted avg       0.83      0.82      0.82       576

VAL * Acc@1 82.465
 * Acc@1 82.465 Acc@5 0.000
accuracy 0.972 	 size: 144 	 dog(outdoor)
accuracy 0.840 	 size: 144 	 cat(indoor)
accuracy 0.812 	 size: 144 	 dog(indoor)
accuracy 0.674 	 size: 144 	 cat(outdoor)
step_vals {'loss': 0.25878795981407166, 'penalty': 0.032396964728832245}
step_vals {'loss': 0.32224300503730774, 'penalty': 0.03128981962800026}
step_vals {'loss': 0.35828089714050293, 'penalty': 0.032611966133117676}
step_vals {'loss': 0.5168973207473755, 'penalty': 0.02560381405055523}
step_vals {'loss': 0.414658784866333, 'penalty': 0.023634513840079308}
step_vals {'loss': 0.30330637097358704, 'penalty': 0.027982059866189957}
step_vals {'loss': 0.37445056438446045, 'penalty': 0.021075598895549774}
step_vals {'loss': 0.4153050184249878, 'penalty': 0.020511645823717117}
step_vals {'loss': 0.3647763133049011, 'penalty': 0.024807479232549667}
step_vals {'loss': 0.3641977906227112, 'penalty': 0.028373686596751213}
step_vals {'loss': 0.3191775679588318, 'penalty': 0.02050563134253025}
step_vals {'loss': 0.3589096963405609, 'penalty': 0.02674127370119095}
step_vals {'loss': 0.36471444368362427, 'penalty': 0.032828252762556076}
step_vals {'loss': 0.34121596813201904, 'penalty': 0.036939382553100586}
step_vals {'loss': 0.2560611367225647, 'penalty': 0.01898336037993431}
step_vals {'loss': 0.2888955771923065, 'penalty': 0.029119348153471947}
step_vals {'loss': 0.4084663987159729, 'penalty': 0.026714541018009186}
step_vals {'loss': 0.3318404257297516, 'penalty': 0.02727339044213295}
step_vals {'loss': 0.3247474431991577, 'penalty': 0.029780365526676178}
step_vals {'loss': 0.48230379819869995, 'penalty': 0.024078065529465675}
Iteration: 60
out-of-domain val
accuracy 0.837 	 roc_auc_score 0.908
confusion_matrix
[[240  48]
 [ 46 242]]
classification_report
              precision    recall  f1-score   support

           0       0.84      0.83      0.84       288
           1       0.83      0.84      0.84       288

    accuracy                           0.84       576
   macro avg       0.84      0.84      0.84       576
weighted avg       0.84      0.84      0.84       576

VAL * Acc@1 83.681
 * Acc@1 83.681 Acc@5 0.000
accuracy 0.910 	 size: 144 	 dog(outdoor)
accuracy 0.896 	 size: 144 	 cat(indoor)
accuracy 0.771 	 size: 144 	 cat(outdoor)
accuracy 0.771 	 size: 144 	 dog(indoor)
step_vals {'loss': 0.3227885663509369, 'penalty': 0.04101790487766266}
step_vals {'loss': 0.20346787571907043, 'penalty': 0.024108098819851875}
step_vals {'loss': 0.3620151877403259, 'penalty': 0.027871448546648026}
step_vals {'loss': 0.3975386917591095, 'penalty': 0.027849946171045303}
step_vals {'loss': 0.21036426723003387, 'penalty': 0.03406856954097748}
step_vals {'loss': 0.33441758155822754, 'penalty': 0.03514659404754639}
step_vals {'loss': 0.47383540868759155, 'penalty': 0.021120574325323105}
step_vals {'loss': 0.20351004600524902, 'penalty': 0.0340735949575901}
step_vals {'loss': 0.29390275478363037, 'penalty': 0.014979745261371136}
step_vals {'loss': 0.3578519821166992, 'penalty': 0.04736859351396561}
step_vals {'loss': 0.20444700121879578, 'penalty': 0.02662714011967182}
step_vals {'loss': 0.34882715344429016, 'penalty': 0.028021149337291718}
step_vals {'loss': 0.3270524740219116, 'penalty': 0.015068717300891876}
step_vals {'loss': 0.24835586547851562, 'penalty': 0.019084541127085686}
step_vals {'loss': 0.3010563850402832, 'penalty': 0.02765093371272087}
step_vals {'loss': 0.27792227268218994, 'penalty': 0.02014658972620964}
step_vals {'loss': 0.2697598934173584, 'penalty': 0.021857241168618202}
step_vals {'loss': 0.27327919006347656, 'penalty': 0.03269461542367935}
step_vals {'loss': 0.28702372312545776, 'penalty': 0.023002872243523598}
step_vals {'loss': 0.20396804809570312, 'penalty': 0.020719463005661964}
Iteration: 80
out-of-domain val
accuracy 0.835 	 roc_auc_score 0.912
confusion_matrix
[[254  34]
 [ 61 227]]
classification_report
              precision    recall  f1-score   support

           0       0.81      0.88      0.84       288
           1       0.87      0.79      0.83       288

    accuracy                           0.84       576
   macro avg       0.84      0.84      0.83       576
weighted avg       0.84      0.84      0.83       576

VAL * Acc@1 83.507
 * Acc@1 83.507 Acc@5 0.000
accuracy 0.931 	 size: 144 	 cat(indoor)
accuracy 0.910 	 size: 144 	 dog(outdoor)
accuracy 0.833 	 size: 144 	 cat(outdoor)
accuracy 0.667 	 size: 144 	 dog(indoor)
