Precision: [tensor(0.2426), tensor(0.5868), tensor(0.2355), tensor(0.5624), tensor(0.5558)]
Output distance: [tensor(5.8210), tensor(5.1326), tensor(5.8351), tensor(5.1814), tensor(5.1945)]
Prediction loss: [tensor(1.9932), tensor(3.8707), tensor(1.9560), tensor(3.8795), tensor(3.6457)]
Others: [{'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)}, {'iter_num': 6, '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(87635.6719), tensor(74350.6875), tensor(86710.2422), tensor(74364.4609), tensor(74760.2578)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=428374), datetime.timedelta(microseconds=472066), datetime.timedelta(microseconds=469213), datetime.timedelta(microseconds=549111), datetime.timedelta(microseconds=465419)]
Phi time: [datetime.timedelta(seconds=10, microseconds=353437), datetime.timedelta(seconds=9, microseconds=939083), datetime.timedelta(seconds=10, microseconds=232236), datetime.timedelta(seconds=9, microseconds=994350), datetime.timedelta(seconds=10, microseconds=457009)]
