Precision: [tensor(0.0239), tensor(0.0255), tensor(0.0226), tensor(0.0294), tensor(0.0249)]
Output distance: [tensor(6.2583), tensor(6.2552), tensor(6.2610), tensor(6.2473), tensor(6.2562)]
Prediction loss: [tensor(2.1295), tensor(2.1808), tensor(2.2996), tensor(2.7576), tensor(2.1359)]
Others: [{'iter_num': 2, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 2, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 2, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 2, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(87489.9219), tensor(87514.2422), tensor(86678.4375), tensor(85495.9531), tensor(86941.5625)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=362225), datetime.timedelta(microseconds=611668), datetime.timedelta(microseconds=473406), datetime.timedelta(microseconds=390533), datetime.timedelta(microseconds=353377)]
Phi time: [datetime.timedelta(seconds=10, microseconds=273297), datetime.timedelta(seconds=10, microseconds=269086), datetime.timedelta(seconds=10, microseconds=992865), datetime.timedelta(seconds=28, microseconds=57877), datetime.timedelta(seconds=10, microseconds=714713)]
