Precision: [tensor(0.5734), tensor(0.2323), tensor(0.2358), tensor(0.2418), tensor(0.2402)]
Output distance: [tensor(5.1594), tensor(5.8414), tensor(5.8346), tensor(5.8225), tensor(5.8257)]
Prediction loss: [tensor(3.8620), tensor(2.0173), tensor(3.1417), tensor(1.9776), tensor(3.1862)]
Others: [{'iter_num': 6, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 6, '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)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(74106.7031), tensor(87289.1953), tensor(88951.0234), tensor(87311.8125), tensor(90000.8594)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=582035), datetime.timedelta(microseconds=572599), datetime.timedelta(microseconds=415668), datetime.timedelta(microseconds=496530), datetime.timedelta(microseconds=491465)]
Phi time: [datetime.timedelta(seconds=10, microseconds=75019), datetime.timedelta(seconds=10, microseconds=305523), datetime.timedelta(seconds=10, microseconds=144696), datetime.timedelta(seconds=10, microseconds=289617), datetime.timedelta(seconds=10, microseconds=133604)]
