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View Code? Open in Web Editor NEWCode for ICML21 spotlight paper "Towards open-world recommendation: An inductive model-based collaborative filtering approach"
Code for ICML21 spotlight paper "Towards open-world recommendation: An inductive model-based collaborative filtering approach"
I'm training ml-1m.
Part of the outputs are shown below:
Epoch 93 Step 76704: Train 0.3622 Reg: 0.4783
Test: 0.9648 MAE: 0.7485 RMSE: 0.9823
Val: 0.9936 MAE: 0.7561 RMSE: 0.9968
Epoch 94 Step 77520: Train 0.3618 Reg: 0.4776
Test: 0.9654 MAE: 0.7486 RMSE: 0.9826
Val: 0.9943 MAE: 0.7562 RMSE: 0.9971
Epoch 95 Step 78336: Train 0.3614 Reg: 0.4769
Test: 0.9659 MAE: 0.7484 RMSE: 0.9828
Val: 0.9948 MAE: 0.7561 RMSE: 0.9974
Epoch 96 Step 79152: Train 0.3611 Reg: 0.4763
Test: 0.9665 MAE: 0.7489 RMSE: 0.9831
Val: 0.9955 MAE: 0.7566 RMSE: 0.9978
Epoch 97 Step 79968: Train 0.3608 Reg: 0.4757
Test: 0.9673 MAE: 0.7495 RMSE: 0.9835
Val: 0.9963 MAE: 0.7572 RMSE: 0.9982
Epoch 98 Step 80784: Train 0.3605 Reg: 0.4751
Test: 0.9676 MAE: 0.7494 RMSE: 0.9837
Val: 0.9967 MAE: 0.7571 RMSE: 0.9983
Epoch 99 Step 81600: Train 0.3603 Reg: 0.4746
Test: 0.9680 MAE: 0.7494 RMSE: 0.9839
Val: 0.9970 MAE: 0.7571 RMSE: 0.9985
As you can see, loss_r_test grew from 0.9648 to 0.9680. In fact, it started to be abnormal after epoch 13.
Epoch 10 Step 8976: Train 0.7002 Reg: 0.5511
Test: 0.7185 MAE: 0.6660 RMSE: 0.8476
Val: 0.7338 MAE: 0.6722 RMSE: 0.8566
Epoch 11 Step 9792: Train 0.6809 Reg: 0.5869
Test: 0.7136 MAE: 0.6643 RMSE: 0.8447
Val: 0.7276 MAE: 0.6705 RMSE: 0.8530
Epoch 12 Step 10608: Train 0.6638 Reg: 0.6277
Test: 0.7109 MAE: 0.6614 RMSE: 0.8431
Val: 0.7244 MAE: 0.6667 RMSE: 0.8511
Epoch 13 Step 11424: Train 0.6438 Reg: 0.6702
Test: 0.7085 MAE: 0.6602 RMSE: 0.8417
Val: 0.7217 MAE: 0.6654 RMSE: 0.8495
Epoch 14 Step 12240: Train 0.6232 Reg: 0.6993
Test: 0.7114 MAE: 0.6602 RMSE: 0.8435
Val: 0.7256 MAE: 0.6661 RMSE: 0.8518
Epoch 15 Step 13056: Train 0.6061 Reg: 0.7176
Test: 0.7164 MAE: 0.6620 RMSE: 0.8464
Val: 0.7304 MAE: 0.6671 RMSE: 0.8547
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