graph nn 10

graph-nn-10.txt

Run experiment on any_cycle1_any_cycleN_10_3_10_1_4
Test set: Average loss: -0.9990, Accuracy: 20000/20000 (100%)
Run experiment on any_cycle1_any_cycleN_10_3_10_2_5
Test set: Average loss: -0.9985, Accuracy: 19997/20000 (100%)
Run experiment on any_cycle1_no_cycleN_10_3_10_1_4
Test set: Average loss: -0.9993, Accuracy: 20000/20000 (100%)
Run experiment on any_cycle1_no_cycleN_10_3_10_2_5
Test set: Average loss: -0.9993, Accuracy: 20000/20000 (100%)
Run experiment on any_cycle1_one_cycleN_10_3_10_1_4
Test set: Average loss: -0.9991, Accuracy: 20000/20000 (100%)
Run experiment on any_cycle1_one_cycleN_10_3_10_2_5
Test set: Average loss: -0.9987, Accuracy: 20000/20000 (100%)
Run experiment on no_cycle1_any_cycleN_10_3_10_1_4
Test set: Average loss: -0.9498, Accuracy: 19297/20000 (96%)
Run experiment on no_cycle1_any_cycleN_10_3_10_2_5
Test set: Average loss: -0.9629, Accuracy: 19472/20000 (97%)
Run experiment on no_cycle1_one_cycleN_10_3_10_1_4
Test set: Average loss: -0.9258, Accuracy: 19790/20000 (99%)
Run experiment on no_cycle1_one_cycleN_10_3_10_2_5
Test set: Average loss: -0.9654, Accuracy: 19987/20000 (100%)
Run experiment on one_cycle1_any_cycleN_10_3_10_1_4
Test set: Average loss: -0.9992, Accuracy: 20000/20000 (100%)
Run experiment on one_cycle1_any_cycleN_10_3_10_2_5
Test set: Average loss: -0.9991, Accuracy: 20000/20000 (100%)
Run experiment on one_cycle1_no_cycleN_10_3_10_1_4
Test set: Average loss: -0.9992, Accuracy: 20000/20000 (100%)
Run experiment on one_cycle1_no_cycleN_10_3_10_2_5
Test set: Average loss: -0.9993, Accuracy: 20000/20000 (100%)
Run experiment on one_cycle1_one_cycleN_10_3_10_1_4
Test set: Average loss: -0.9993, Accuracy: 20000/20000 (100%)
Run experiment on one_cycle1_one_cycleN_10_3_10_2_5
Test set: Average loss: -0.9992, Accuracy: 20000/20000 (100%)