Precision: [tensor(0.2239), tensor(0.2310), tensor(0.5582), tensor(0.2250), tensor(0.5797)]
Output distance: [tensor(5.8582), tensor(5.8441), tensor(5.1898), tensor(5.8561), tensor(5.1468)]
Prediction loss: [tensor(3.1095), tensor(2.0043), tensor(3.8598), tensor(3.1968), tensor(3.8405)]
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(89120.8125), tensor(87409.2656), tensor(74209.1094), tensor(88962.0391), tensor(74018.4688)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=807239), datetime.timedelta(microseconds=797237), datetime.timedelta(microseconds=653735), datetime.timedelta(microseconds=663662), datetime.timedelta(microseconds=789464)]
Phi time: [datetime.timedelta(seconds=10, microseconds=770624), datetime.timedelta(seconds=10, microseconds=627208), datetime.timedelta(seconds=10, microseconds=609956), datetime.timedelta(seconds=9, microseconds=606054), datetime.timedelta(seconds=10, microseconds=653436)]
