Precision: [tensor(0.5432), tensor(0.5613), tensor(0.2056), tensor(0.2274), tensor(0.2171)]
Output distance: [tensor(5.2197), tensor(5.1835), tensor(5.8950), tensor(5.8514), tensor(5.8719)]
Prediction loss: [tensor(3.3499), tensor(3.8213), tensor(2.0045), tensor(1.9981), tensor(2.0251)]
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': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 6, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(75760.2109), tensor(74123.8047), tensor(87291.8984), tensor(87167.4453), tensor(86798.8906)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=475923), datetime.timedelta(microseconds=471809), datetime.timedelta(microseconds=392349), datetime.timedelta(microseconds=469526), datetime.timedelta(microseconds=554927)]
Phi time: [datetime.timedelta(seconds=9, microseconds=408008), datetime.timedelta(seconds=9, microseconds=998985), datetime.timedelta(seconds=9, microseconds=286209), datetime.timedelta(seconds=10, microseconds=301135), datetime.timedelta(seconds=9, microseconds=196161)]
