Precision: [tensor(0.2389), tensor(0.5723), tensor(0.2468), tensor(0.2329), tensor(0.2400)]
Output distance: [tensor(5.8283), tensor(5.1615), tensor(5.8125), tensor(5.8404), tensor(5.8262)]
Prediction loss: [tensor(2.0519), tensor(4.3536), tensor(3.2181), tensor(2.0122), tensor(3.0211)]
Others: [{'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(87488.3906), tensor(73465.7812), tensor(89109.9375), tensor(87307.7500), tensor(89068.2422)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=465350), datetime.timedelta(microseconds=464165), datetime.timedelta(microseconds=389929), datetime.timedelta(microseconds=387922), datetime.timedelta(microseconds=467377)]
Phi time: [datetime.timedelta(seconds=10, microseconds=357007), datetime.timedelta(seconds=9, microseconds=984266), datetime.timedelta(seconds=9, microseconds=705588), datetime.timedelta(seconds=10, microseconds=323608), datetime.timedelta(seconds=10, microseconds=175711)]
