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TA_P_ensemble.out
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An import exception occurred
loaded dataset: ogbn-products
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 564271
Start running train at 05-14 03:33:59
Epoch: 0, Time: 0.7218, Loss: 3.9210, TrainAcc: 0.0078, ValAcc: 0.2971, ES: 00/50 | BestVal=0.2971@E0
Epoch: 10, Time: 0.0521, Loss: 0.9144, TrainAcc: 0.7401, ValAcc: 0.7665, ES: 00/50 | BestVal=0.7665@E10
Epoch: 20, Time: 0.0533, Loss: 0.7971, TrainAcc: 0.7630, ValAcc: 0.7913, ES: 01/50 | BestVal=0.7920@E19
Epoch: 30, Time: 0.0570, Loss: 0.7501, TrainAcc: 0.7689, ValAcc: 0.7977, ES: 02/50 | BestVal=0.7983@E28
Epoch: 40, Time: 0.0641, Loss: 0.7164, TrainAcc: 0.7765, ValAcc: 0.8034, ES: 00/50 | BestVal=0.8034@E40
Epoch: 50, Time: 0.0586, Loss: 0.6876, TrainAcc: 0.7849, ValAcc: 0.8117, ES: 00/50 | BestVal=0.8117@E50
Epoch: 60, Time: 0.0561, Loss: 0.6610, TrainAcc: 0.7896, ValAcc: 0.8066, ES: 09/50 | BestVal=0.8117@E51
Epoch: 70, Time: 0.0548, Loss: 0.6364, TrainAcc: 0.7975, ValAcc: 0.8028, ES: 02/50 | BestVal=0.8136@E68
Epoch: 80, Time: 0.0543, Loss: 0.6119, TrainAcc: 0.8037, ValAcc: 0.7926, ES: 05/50 | BestVal=0.8142@E75
Epoch: 90, Time: 0.0550, Loss: 0.5999, TrainAcc: 0.8056, ValAcc: 0.7971, ES: 07/50 | BestVal=0.8200@E83
Epoch: 100, Time: 0.0520, Loss: 0.5710, TrainAcc: 0.8152, ValAcc: 0.8009, ES: 17/50 | BestVal=0.8200@E83
Epoch: 110, Time: 0.0514, Loss: 0.5490, TrainAcc: 0.8200, ValAcc: 0.7907, ES: 27/50 | BestVal=0.8200@E83
Epoch: 120, Time: 0.0571, Loss: 0.5383, TrainAcc: 0.8252, ValAcc: 0.7971, ES: 37/50 | BestVal=0.8200@E83
Epoch: 130, Time: 0.0562, Loss: 0.5184, TrainAcc: 0.8292, ValAcc: 0.7958, ES: 47/50 | BestVal=0.8200@E83
Early stopped, loading model from epoch-83
Finished running train at 05-14 03:34:07, running time = 8.07s.
[RevGAT + TA] ValAcc: 0.8200, TestAcc: 0.7263
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Loading model GCN...
Number of parameters: 564271
Start running train at 05-14 03:34:08
Epoch: 0, Time: 0.1026, Loss: 4.4346, TrainAcc: 0.0109, ValAcc: 0.6393, ES: 00/50 | BestVal=0.6393@E0
Epoch: 10, Time: 0.0728, Loss: 0.7401, TrainAcc: 0.8233, ValAcc: 0.8225, ES: 00/50 | BestVal=0.8225@E10
Epoch: 20, Time: 0.0718, Loss: 0.6253, TrainAcc: 0.8373, ValAcc: 0.8461, ES: 00/50 | BestVal=0.8461@E20
Epoch: 30, Time: 0.0671, Loss: 0.5686, TrainAcc: 0.8504, ValAcc: 0.8601, ES: 01/50 | BestVal=0.8613@E29
Epoch: 40, Time: 0.0674, Loss: 0.5290, TrainAcc: 0.8579, ValAcc: 0.8690, ES: 01/50 | BestVal=0.8702@E39
Epoch: 50, Time: 0.0700, Loss: 0.4957, TrainAcc: 0.8631, ValAcc: 0.8461, ES: 01/50 | BestVal=0.8721@E49
Epoch: 60, Time: 0.0731, Loss: 0.4928, TrainAcc: 0.8491, ValAcc: 0.8715, ES: 11/50 | BestVal=0.8721@E49
Epoch: 70, Time: 0.0728, Loss: 0.4528, TrainAcc: 0.8706, ValAcc: 0.8702, ES: 21/50 | BestVal=0.8721@E49
Epoch: 80, Time: 0.0711, Loss: 0.4178, TrainAcc: 0.8780, ValAcc: 0.8760, ES: 05/50 | BestVal=0.8772@E75
Epoch: 90, Time: 0.0694, Loss: 0.3905, TrainAcc: 0.8879, ValAcc: 0.8683, ES: 15/50 | BestVal=0.8772@E75
Epoch: 100, Time: 0.0696, Loss: 0.3715, TrainAcc: 0.8866, ValAcc: 0.8734, ES: 02/50 | BestVal=0.8791@E98
Epoch: 110, Time: 0.0711, Loss: 0.3648, TrainAcc: 0.8820, ValAcc: 0.8791, ES: 05/50 | BestVal=0.8880@E105
Epoch: 120, Time: 0.0715, Loss: 0.3184, TrainAcc: 0.9042, ValAcc: 0.8842, ES: 03/50 | BestVal=0.8880@E117
Epoch: 130, Time: 0.0701, Loss: 0.3148, TrainAcc: 0.9060, ValAcc: 0.8690, ES: 06/50 | BestVal=0.8899@E124
Epoch: 140, Time: 0.0695, Loss: 0.2840, TrainAcc: 0.9117, ValAcc: 0.8658, ES: 16/50 | BestVal=0.8899@E124
Epoch: 150, Time: 0.0712, Loss: 0.2598, TrainAcc: 0.9214, ValAcc: 0.8810, ES: 09/50 | BestVal=0.8925@E141
Epoch: 160, Time: 0.0707, Loss: 0.2896, TrainAcc: 0.9134, ValAcc: 0.8836, ES: 19/50 | BestVal=0.8925@E141
Epoch: 170, Time: 0.0700, Loss: 0.2407, TrainAcc: 0.9251, ValAcc: 0.8855, ES: 29/50 | BestVal=0.8925@E141
Epoch: 180, Time: 0.0733, Loss: 0.3312, TrainAcc: 0.8884, ValAcc: 0.8645, ES: 39/50 | BestVal=0.8925@E141
Epoch: 190, Time: 0.0730, Loss: 0.2500, TrainAcc: 0.9183, ValAcc: 0.8645, ES: 49/50 | BestVal=0.8925@E141
Early stopped, loading model from epoch-141
Finished running train at 05-14 03:34:22, running time = 13.70s.
[GCN + TA] ValAcc: 0.8925, TestAcc: 0.7768
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Loading model SAGE...
Number of parameters: 1127343
Start running train at 05-14 03:34:23
Epoch: 0, Time: 0.2035, Loss: 3.9617, TrainAcc: 0.0470, ValAcc: 0.3976, ES: 00/50 | BestVal=0.3976@E0
Epoch: 10, Time: 0.1870, Loss: 0.7697, TrainAcc: 0.8080, ValAcc: 0.7754, ES: 00/50 | BestVal=0.7754@E10
Epoch: 20, Time: 0.1875, Loss: 0.6401, TrainAcc: 0.8304, ValAcc: 0.8270, ES: 00/50 | BestVal=0.8270@E20
Epoch: 30, Time: 0.1868, Loss: 0.5559, TrainAcc: 0.8475, ValAcc: 0.8632, ES: 00/50 | BestVal=0.8632@E30
Epoch: 40, Time: 0.1888, Loss: 0.4945, TrainAcc: 0.8610, ValAcc: 0.8753, ES: 00/50 | BestVal=0.8753@E40
Epoch: 50, Time: 0.1831, Loss: 0.4708, TrainAcc: 0.8546, ValAcc: 0.8562, ES: 03/50 | BestVal=0.8785@E47
Epoch: 60, Time: 0.1862, Loss: 0.4143, TrainAcc: 0.8801, ValAcc: 0.8760, ES: 06/50 | BestVal=0.8785@E54
Epoch: 70, Time: 0.1871, Loss: 0.3566, TrainAcc: 0.8994, ValAcc: 0.8849, ES: 00/50 | BestVal=0.8849@E70
Epoch: 80, Time: 0.1865, Loss: 0.3210, TrainAcc: 0.9104, ValAcc: 0.8925, ES: 03/50 | BestVal=0.8931@E77
Epoch: 90, Time: 0.1842, Loss: 0.2870, TrainAcc: 0.9151, ValAcc: 0.8880, ES: 06/50 | BestVal=0.8963@E84
Epoch: 100, Time: 0.1967, Loss: 0.2575, TrainAcc: 0.9226, ValAcc: 0.9001, ES: 00/50 | BestVal=0.9001@E100
Epoch: 110, Time: 0.1861, Loss: 0.2446, TrainAcc: 0.9296, ValAcc: 0.8982, ES: 04/50 | BestVal=0.9020@E106
Epoch: 120, Time: 0.1902, Loss: 0.2307, TrainAcc: 0.9213, ValAcc: 0.8976, ES: 14/50 | BestVal=0.9020@E106
Epoch: 130, Time: 0.1896, Loss: 0.1838, TrainAcc: 0.9445, ValAcc: 0.9027, ES: 07/50 | BestVal=0.9052@E123
Epoch: 140, Time: 0.1891, Loss: 0.1554, TrainAcc: 0.9536, ValAcc: 0.8969, ES: 09/50 | BestVal=0.9065@E131
Epoch: 150, Time: 0.1895, Loss: 0.1366, TrainAcc: 0.9629, ValAcc: 0.8899, ES: 19/50 | BestVal=0.9065@E131
Epoch: 160, Time: 0.1934, Loss: 0.1086, TrainAcc: 0.9712, ValAcc: 0.9001, ES: 29/50 | BestVal=0.9065@E131
Epoch: 170, Time: 0.1913, Loss: 0.1300, TrainAcc: 0.9567, ValAcc: 0.8798, ES: 39/50 | BestVal=0.9065@E131
Epoch: 180, Time: 0.1896, Loss: 0.1513, TrainAcc: 0.9547, ValAcc: 0.8880, ES: 49/50 | BestVal=0.9065@E131
Early stopped, loading model from epoch-131
Finished running train at 05-14 03:34:57, running time = 34.23s.
[SAGE + TA] ValAcc: 0.9065, TestAcc: 0.7948
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Loading model MLP...
Number of parameters: 564271
Start running train at 05-14 03:34:58
Epoch: 0, Time: 0.0485, Loss: 3.9346, TrainAcc: 0.0088, ValAcc: 0.2576, ES: 00/50 | BestVal=0.2576@E0
Epoch: 10, Time: 0.0610, Loss: 0.9146, TrainAcc: 0.7327, ValAcc: 0.7678, ES: 00/50 | BestVal=0.7678@E10
Epoch: 20, Time: 0.0614, Loss: 0.7894, TrainAcc: 0.7583, ValAcc: 0.7958, ES: 00/50 | BestVal=0.7958@E20
Epoch: 30, Time: 0.0571, Loss: 0.7402, TrainAcc: 0.7723, ValAcc: 0.8028, ES: 01/50 | BestVal=0.8034@E29
Epoch: 40, Time: 0.0590, Loss: 0.7075, TrainAcc: 0.7800, ValAcc: 0.7939, ES: 11/50 | BestVal=0.8034@E29
Epoch: 50, Time: 0.0615, Loss: 0.6784, TrainAcc: 0.7860, ValAcc: 0.7983, ES: 21/50 | BestVal=0.8034@E29
Epoch: 60, Time: 0.0621, Loss: 0.6524, TrainAcc: 0.7939, ValAcc: 0.8047, ES: 00/50 | BestVal=0.8047@E60
Epoch: 70, Time: 0.0614, Loss: 0.6288, TrainAcc: 0.7986, ValAcc: 0.8009, ES: 07/50 | BestVal=0.8053@E63
Epoch: 80, Time: 0.0574, Loss: 0.6053, TrainAcc: 0.8049, ValAcc: 0.8009, ES: 02/50 | BestVal=0.8073@E78
Epoch: 90, Time: 0.0615, Loss: 0.5865, TrainAcc: 0.8104, ValAcc: 0.8003, ES: 12/50 | BestVal=0.8073@E78
Epoch: 100, Time: 0.0611, Loss: 0.5599, TrainAcc: 0.8171, ValAcc: 0.8028, ES: 22/50 | BestVal=0.8073@E78
Epoch: 110, Time: 0.0605, Loss: 0.5567, TrainAcc: 0.8156, ValAcc: 0.7913, ES: 05/50 | BestVal=0.8073@E105
Epoch: 120, Time: 0.0616, Loss: 0.5282, TrainAcc: 0.8274, ValAcc: 0.7996, ES: 15/50 | BestVal=0.8073@E105
Epoch: 130, Time: 0.0606, Loss: 0.5117, TrainAcc: 0.8325, ValAcc: 0.7907, ES: 25/50 | BestVal=0.8073@E105
Epoch: 140, Time: 0.0611, Loss: 0.5317, TrainAcc: 0.8253, ValAcc: 0.7983, ES: 35/50 | BestVal=0.8073@E105
Epoch: 150, Time: 0.0607, Loss: 0.5028, TrainAcc: 0.8341, ValAcc: 0.7958, ES: 45/50 | BestVal=0.8073@E105
Early stopped, loading model from epoch-105
Finished running train at 05-14 03:35:08, running time = 9.45s.
[MLP + TA] ValAcc: 0.8073, TestAcc: 0.7204
Loading top-k prediction features ...
Loading topk preds from gpt_preds/ogbn-products.csv
An import exception occurred
loaded dataset: ogbn-products
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 564271
Start running train at 05-14 03:35:15
Epoch: 0, Time: 0.7085, Loss: 3.9231, TrainAcc: 0.0307, ValAcc: 0.2424, ES: 00/50 | BestVal=0.2424@E0
Epoch: 10, Time: 0.0591, Loss: 0.9302, TrainAcc: 0.7380, ValAcc: 0.7595, ES: 00/50 | BestVal=0.7595@E10
Epoch: 20, Time: 0.0599, Loss: 0.8079, TrainAcc: 0.7618, ValAcc: 0.7894, ES: 00/50 | BestVal=0.7894@E20
Epoch: 30, Time: 0.0544, Loss: 0.7478, TrainAcc: 0.7718, ValAcc: 0.7844, ES: 01/50 | BestVal=0.7977@E29
Epoch: 40, Time: 0.0599, Loss: 0.7103, TrainAcc: 0.7789, ValAcc: 0.7901, ES: 11/50 | BestVal=0.7977@E29
Epoch: 50, Time: 0.0526, Loss: 0.6756, TrainAcc: 0.7867, ValAcc: 0.7971, ES: 03/50 | BestVal=0.7983@E47
Epoch: 60, Time: 0.0548, Loss: 0.6425, TrainAcc: 0.7898, ValAcc: 0.8022, ES: 01/50 | BestVal=0.8149@E59
Epoch: 70, Time: 0.0593, Loss: 0.6089, TrainAcc: 0.7983, ValAcc: 0.8003, ES: 08/50 | BestVal=0.8168@E62
Epoch: 80, Time: 0.0571, Loss: 0.5853, TrainAcc: 0.8138, ValAcc: 0.8155, ES: 18/50 | BestVal=0.8168@E62
Epoch: 90, Time: 0.0598, Loss: 0.5520, TrainAcc: 0.8237, ValAcc: 0.7971, ES: 28/50 | BestVal=0.8168@E62
Epoch: 100, Time: 0.0535, Loss: 0.5231, TrainAcc: 0.8300, ValAcc: 0.7907, ES: 38/50 | BestVal=0.8168@E62
Epoch: 110, Time: 0.0609, Loss: 0.5031, TrainAcc: 0.8357, ValAcc: 0.7920, ES: 48/50 | BestVal=0.8168@E62
Early stopped, loading model from epoch-62
Finished running train at 05-14 03:35:22, running time = 7.30s.
[RevGAT + TA] ValAcc: 0.8168, TestAcc: 0.7252
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Loading model GCN...
Number of parameters: 564271
Start running train at 05-14 03:35:23
Epoch: 0, Time: 0.1136, Loss: 3.9323, TrainAcc: 0.0442, ValAcc: 0.5165, ES: 00/50 | BestVal=0.5165@E0
Epoch: 10, Time: 0.0699, Loss: 0.7343, TrainAcc: 0.8179, ValAcc: 0.7977, ES: 04/50 | BestVal=0.8022@E6
Epoch: 20, Time: 0.0720, Loss: 0.6192, TrainAcc: 0.8402, ValAcc: 0.8607, ES: 00/50 | BestVal=0.8607@E20
Epoch: 30, Time: 0.0764, Loss: 0.5576, TrainAcc: 0.8515, ValAcc: 0.8620, ES: 02/50 | BestVal=0.8677@E28
Epoch: 40, Time: 0.0723, Loss: 0.5118, TrainAcc: 0.8578, ValAcc: 0.8632, ES: 12/50 | BestVal=0.8677@E28
Epoch: 50, Time: 0.0699, Loss: 0.4710, TrainAcc: 0.8708, ValAcc: 0.8562, ES: 22/50 | BestVal=0.8677@E28
Epoch: 60, Time: 0.0743, Loss: 0.4344, TrainAcc: 0.8771, ValAcc: 0.8588, ES: 32/50 | BestVal=0.8677@E28
Epoch: 70, Time: 0.0715, Loss: 0.4492, TrainAcc: 0.8697, ValAcc: 0.8193, ES: 42/50 | BestVal=0.8677@E28
Epoch: 80, Time: 0.0742, Loss: 0.3869, TrainAcc: 0.8835, ValAcc: 0.8817, ES: 00/50 | BestVal=0.8817@E80
Epoch: 90, Time: 0.0707, Loss: 0.3457, TrainAcc: 0.9005, ValAcc: 0.8810, ES: 09/50 | BestVal=0.8823@E81
Epoch: 100, Time: 0.0730, Loss: 0.3033, TrainAcc: 0.9102, ValAcc: 0.8683, ES: 19/50 | BestVal=0.8823@E81
Epoch: 110, Time: 0.0715, Loss: 0.3119, TrainAcc: 0.9037, ValAcc: 0.8709, ES: 05/50 | BestVal=0.8868@E105
Epoch: 120, Time: 0.0723, Loss: 0.2554, TrainAcc: 0.9260, ValAcc: 0.8429, ES: 15/50 | BestVal=0.8868@E105
Epoch: 130, Time: 0.0804, Loss: 0.2271, TrainAcc: 0.9309, ValAcc: 0.8887, ES: 00/50 | BestVal=0.8887@E130
Epoch: 140, Time: 0.0747, Loss: 0.2353, TrainAcc: 0.9268, ValAcc: 0.8785, ES: 10/50 | BestVal=0.8887@E130
Epoch: 150, Time: 0.0755, Loss: 0.1802, TrainAcc: 0.9466, ValAcc: 0.8817, ES: 20/50 | BestVal=0.8887@E130
Epoch: 160, Time: 0.0747, Loss: 0.1856, TrainAcc: 0.9398, ValAcc: 0.8613, ES: 30/50 | BestVal=0.8887@E130
Epoch: 170, Time: 0.0712, Loss: 0.2607, TrainAcc: 0.9256, ValAcc: 0.8562, ES: 40/50 | BestVal=0.8887@E130
Early stopped, loading model from epoch-130
Finished running train at 05-14 03:35:36, running time = 13.25s.
[GCN + TA] ValAcc: 0.8887, TestAcc: 0.7744
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Loading model SAGE...
Number of parameters: 1127343
Start running train at 05-14 03:35:37
Epoch: 0, Time: 0.2032, Loss: 4.1306, TrainAcc: 0.0064, ValAcc: 0.1616, ES: 00/50 | BestVal=0.1616@E0
Epoch: 10, Time: 0.1930, Loss: 0.7834, TrainAcc: 0.7987, ValAcc: 0.7697, ES: 00/50 | BestVal=0.7697@E10
Epoch: 20, Time: 0.1953, Loss: 0.6464, TrainAcc: 0.8318, ValAcc: 0.8092, ES: 00/50 | BestVal=0.8092@E20
Epoch: 30, Time: 0.1827, Loss: 0.5449, TrainAcc: 0.8563, ValAcc: 0.8403, ES: 01/50 | BestVal=0.8429@E29
Epoch: 40, Time: 0.1964, Loss: 0.5119, TrainAcc: 0.8434, ValAcc: 0.8664, ES: 00/50 | BestVal=0.8664@E40
Epoch: 50, Time: 0.1853, Loss: 0.4344, TrainAcc: 0.8812, ValAcc: 0.8753, ES: 04/50 | BestVal=0.8766@E46
Epoch: 60, Time: 0.1897, Loss: 0.3828, TrainAcc: 0.8934, ValAcc: 0.8823, ES: 03/50 | BestVal=0.8855@E57
Epoch: 70, Time: 0.1832, Loss: 0.3606, TrainAcc: 0.8993, ValAcc: 0.8569, ES: 01/50 | BestVal=0.8893@E69
Epoch: 80, Time: 0.1854, Loss: 0.3080, TrainAcc: 0.9100, ValAcc: 0.8849, ES: 11/50 | BestVal=0.8893@E69
Epoch: 90, Time: 0.1909, Loss: 0.2583, TrainAcc: 0.9251, ValAcc: 0.8899, ES: 06/50 | BestVal=0.8963@E84
Epoch: 100, Time: 0.1864, Loss: 0.2766, TrainAcc: 0.9207, ValAcc: 0.8836, ES: 16/50 | BestVal=0.8963@E84
Epoch: 110, Time: 0.1867, Loss: 0.2137, TrainAcc: 0.9373, ValAcc: 0.8957, ES: 26/50 | BestVal=0.8963@E84
Epoch: 120, Time: 0.1849, Loss: 0.1745, TrainAcc: 0.9507, ValAcc: 0.8868, ES: 08/50 | BestVal=0.8982@E112
Epoch: 130, Time: 0.1850, Loss: 0.1696, TrainAcc: 0.9515, ValAcc: 0.8868, ES: 18/50 | BestVal=0.8982@E112
Epoch: 140, Time: 0.1868, Loss: 0.1273, TrainAcc: 0.9653, ValAcc: 0.8938, ES: 28/50 | BestVal=0.8982@E112
Epoch: 150, Time: 0.1883, Loss: 0.1018, TrainAcc: 0.9736, ValAcc: 0.8874, ES: 38/50 | BestVal=0.8982@E112
Epoch: 160, Time: 0.1880, Loss: 0.0788, TrainAcc: 0.9812, ValAcc: 0.8938, ES: 48/50 | BestVal=0.8982@E112
Early stopped, loading model from epoch-112
Finished running train at 05-14 03:36:08, running time = 30.74s.
[SAGE + TA] ValAcc: 0.8982, TestAcc: 0.7833
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/ogbn-products/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([54025, 4096])
Loading model MLP...
Number of parameters: 564271
Start running train at 05-14 03:36:09
Epoch: 0, Time: 0.0472, Loss: 4.0424, TrainAcc: 0.0037, ValAcc: 0.2761, ES: 00/50 | BestVal=0.2761@E0
Epoch: 10, Time: 0.0596, Loss: 0.9195, TrainAcc: 0.7302, ValAcc: 0.7557, ES: 00/50 | BestVal=0.7557@E10
Epoch: 20, Time: 0.0583, Loss: 0.8015, TrainAcc: 0.7618, ValAcc: 0.7799, ES: 04/50 | BestVal=0.7812@E16
Epoch: 30, Time: 0.0627, Loss: 0.7493, TrainAcc: 0.7707, ValAcc: 0.7837, ES: 00/50 | BestVal=0.7837@E30
Epoch: 40, Time: 0.0612, Loss: 0.7111, TrainAcc: 0.7792, ValAcc: 0.7901, ES: 00/50 | BestVal=0.7901@E40
Epoch: 50, Time: 0.0597, Loss: 0.6773, TrainAcc: 0.7864, ValAcc: 0.7939, ES: 02/50 | BestVal=0.7952@E48
Epoch: 60, Time: 0.0662, Loss: 0.6456, TrainAcc: 0.7941, ValAcc: 0.7958, ES: 00/50 | BestVal=0.7958@E60
Epoch: 70, Time: 0.0599, Loss: 0.6116, TrainAcc: 0.8036, ValAcc: 0.7964, ES: 00/50 | BestVal=0.7964@E70
Epoch: 80, Time: 0.0639, Loss: 0.5774, TrainAcc: 0.8131, ValAcc: 0.8015, ES: 00/50 | BestVal=0.8015@E80
Epoch: 90, Time: 0.0618, Loss: 0.5480, TrainAcc: 0.8224, ValAcc: 0.7958, ES: 08/50 | BestVal=0.8142@E82
Epoch: 100, Time: 0.0599, Loss: 0.5193, TrainAcc: 0.8315, ValAcc: 0.8111, ES: 18/50 | BestVal=0.8142@E82
Epoch: 110, Time: 0.0612, Loss: 0.5331, TrainAcc: 0.8310, ValAcc: 0.8009, ES: 28/50 | BestVal=0.8142@E82
Epoch: 120, Time: 0.0584, Loss: 0.5113, TrainAcc: 0.8342, ValAcc: 0.7939, ES: 38/50 | BestVal=0.8142@E82
Epoch: 130, Time: 0.0606, Loss: 0.4879, TrainAcc: 0.8401, ValAcc: 0.7990, ES: 48/50 | BestVal=0.8142@E82
Early stopped, loading model from epoch-82
Finished running train at 05-14 03:36:17, running time = 7.93s.
[MLP + TA] ValAcc: 0.8142, TestAcc: 0.7242
Loading top-k prediction features ...
Loading topk preds from gpt_preds/ogbn-products.csv
An import exception occurred
loaded dataset: cora
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 559111
Start running train at 05-14 03:36:32
Epoch: 0, Time: 1.0158, Loss: 1.9726, TrainAcc: 0.1669, ValAcc: 0.1808, ES: 00/50 | BestVal=0.1808@E0
Epoch: 10, Time: 0.0119, Loss: 0.6978, TrainAcc: 0.7783, ValAcc: 0.6236, ES: 00/50 | BestVal=0.6236@E10
Epoch: 20, Time: 0.0120, Loss: 0.5573, TrainAcc: 0.8282, ValAcc: 0.7066, ES: 00/50 | BestVal=0.7066@E20
Epoch: 30, Time: 0.0061, Loss: 0.4623, TrainAcc: 0.8522, ValAcc: 0.7103, ES: 01/50 | BestVal=0.7214@E29
Epoch: 40, Time: 0.0111, Loss: 0.3314, TrainAcc: 0.8812, ValAcc: 0.7694, ES: 00/50 | BestVal=0.7694@E40
Epoch: 50, Time: 0.0062, Loss: 0.2270, TrainAcc: 0.9243, ValAcc: 0.7399, ES: 10/50 | BestVal=0.7694@E40
Epoch: 60, Time: 0.0049, Loss: 0.2256, TrainAcc: 0.9212, ValAcc: 0.7638, ES: 20/50 | BestVal=0.7694@E40
Epoch: 70, Time: 0.0047, Loss: 0.1104, TrainAcc: 0.9674, ValAcc: 0.7362, ES: 30/50 | BestVal=0.7694@E40
Epoch: 80, Time: 0.0048, Loss: 0.0604, TrainAcc: 0.9877, ValAcc: 0.7565, ES: 40/50 | BestVal=0.7694@E40
Epoch: 90, Time: 0.0047, Loss: 0.0375, TrainAcc: 0.9920, ValAcc: 0.7694, ES: 04/50 | BestVal=0.7712@E86
Epoch: 100, Time: 0.0047, Loss: 0.0159, TrainAcc: 0.9969, ValAcc: 0.7749, ES: 01/50 | BestVal=0.7786@E99
Epoch: 110, Time: 0.0044, Loss: 0.0067, TrainAcc: 1.0000, ValAcc: 0.7768, ES: 04/50 | BestVal=0.7915@E106
Epoch: 120, Time: 0.0044, Loss: 0.0035, TrainAcc: 1.0000, ValAcc: 0.7694, ES: 14/50 | BestVal=0.7915@E106
Epoch: 130, Time: 0.0044, Loss: 0.0021, TrainAcc: 1.0000, ValAcc: 0.7712, ES: 24/50 | BestVal=0.7915@E106
Epoch: 140, Time: 0.0044, Loss: 0.0015, TrainAcc: 1.0000, ValAcc: 0.7675, ES: 34/50 | BestVal=0.7915@E106
Epoch: 150, Time: 0.0044, Loss: 0.0012, TrainAcc: 1.0000, ValAcc: 0.7694, ES: 44/50 | BestVal=0.7915@E106
Early stopped, loading model from epoch-106
Finished running train at 05-14 03:36:34, running time = 2.01s.
[RevGAT + TA] ValAcc: 0.7915, TestAcc: 0.7232
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Loading model GCN...
Number of parameters: 559111
Start running train at 05-14 03:36:38
Epoch: 0, Time: 0.0188, Loss: 2.3522, TrainAcc: 0.0998, ValAcc: 0.2934, ES: 00/50 | BestVal=0.2934@E0
Epoch: 10, Time: 0.0150, Loss: 0.4661, TrainAcc: 0.8454, ValAcc: 0.7122, ES: 00/50 | BestVal=0.7122@E10
Epoch: 20, Time: 0.0145, Loss: 0.3850, TrainAcc: 0.8615, ValAcc: 0.7804, ES: 00/50 | BestVal=0.7804@E20
Epoch: 30, Time: 0.0128, Loss: 0.3296, TrainAcc: 0.8762, ValAcc: 0.8081, ES: 00/50 | BestVal=0.8081@E30
Epoch: 40, Time: 0.0069, Loss: 0.2789, TrainAcc: 0.8966, ValAcc: 0.8469, ES: 01/50 | BestVal=0.8506@E39
Epoch: 50, Time: 0.0064, Loss: 0.2600, TrainAcc: 0.9064, ValAcc: 0.8284, ES: 02/50 | BestVal=0.8653@E48
Epoch: 60, Time: 0.0066, Loss: 0.2114, TrainAcc: 0.9218, ValAcc: 0.8708, ES: 09/50 | BestVal=0.8819@E51
Epoch: 70, Time: 0.0064, Loss: 0.1927, TrainAcc: 0.9280, ValAcc: 0.8745, ES: 04/50 | BestVal=0.8911@E66
Epoch: 80, Time: 0.0065, Loss: 0.1641, TrainAcc: 0.9464, ValAcc: 0.8745, ES: 06/50 | BestVal=0.8911@E74
Epoch: 90, Time: 0.0065, Loss: 0.1958, TrainAcc: 0.9261, ValAcc: 0.8081, ES: 16/50 | BestVal=0.8911@E74
Epoch: 100, Time: 0.0064, Loss: 0.1696, TrainAcc: 0.9366, ValAcc: 0.8764, ES: 26/50 | BestVal=0.8911@E74
Epoch: 110, Time: 0.0064, Loss: 0.1380, TrainAcc: 0.9477, ValAcc: 0.8690, ES: 36/50 | BestVal=0.8911@E74
Epoch: 120, Time: 0.0063, Loss: 0.1092, TrainAcc: 0.9612, ValAcc: 0.8672, ES: 46/50 | BestVal=0.8911@E74
Early stopped, loading model from epoch-74
Finished running train at 05-14 03:36:39, running time = 1.09s.
[GCN + TA] ValAcc: 0.8911, TestAcc: 0.8635
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Loading model SAGE...
Number of parameters: 1117063
Start running train at 05-14 03:36:42
Epoch: 0, Time: 0.0417, Loss: 1.9415, TrainAcc: 0.2654, ValAcc: 0.3727, ES: 00/50 | BestVal=0.3727@E0
Epoch: 10, Time: 0.0177, Loss: 0.4851, TrainAcc: 0.8294, ValAcc: 0.6181, ES: 01/50 | BestVal=0.6310@E9
Epoch: 20, Time: 0.0245, Loss: 0.3997, TrainAcc: 0.8553, ValAcc: 0.7472, ES: 00/50 | BestVal=0.7472@E20
Epoch: 30, Time: 0.0247, Loss: 0.3375, TrainAcc: 0.8756, ValAcc: 0.8155, ES: 00/50 | BestVal=0.8155@E30
Epoch: 40, Time: 0.0159, Loss: 0.2861, TrainAcc: 0.8966, ValAcc: 0.8450, ES: 01/50 | BestVal=0.8469@E39
Epoch: 50, Time: 0.0158, Loss: 0.2522, TrainAcc: 0.9126, ValAcc: 0.8487, ES: 03/50 | BestVal=0.8672@E47
Epoch: 60, Time: 0.0162, Loss: 0.2151, TrainAcc: 0.9212, ValAcc: 0.8524, ES: 13/50 | BestVal=0.8672@E47
Epoch: 70, Time: 0.0173, Loss: 0.2323, TrainAcc: 0.9107, ValAcc: 0.8487, ES: 23/50 | BestVal=0.8672@E47
Epoch: 80, Time: 0.0161, Loss: 0.1534, TrainAcc: 0.9514, ValAcc: 0.8653, ES: 02/50 | BestVal=0.8764@E78
Epoch: 90, Time: 0.0165, Loss: 0.1303, TrainAcc: 0.9544, ValAcc: 0.8487, ES: 12/50 | BestVal=0.8764@E78
Epoch: 100, Time: 0.0165, Loss: 0.1120, TrainAcc: 0.9618, ValAcc: 0.8653, ES: 22/50 | BestVal=0.8764@E78
Epoch: 110, Time: 0.0163, Loss: 0.0799, TrainAcc: 0.9748, ValAcc: 0.8635, ES: 32/50 | BestVal=0.8764@E78
Epoch: 120, Time: 0.0163, Loss: 0.3321, TrainAcc: 0.9089, ValAcc: 0.8303, ES: 42/50 | BestVal=0.8764@E78
Early stopped, loading model from epoch-78
Finished running train at 05-14 03:36:45, running time = 2.57s.
[SAGE + TA] ValAcc: 0.8764, TestAcc: 0.8635
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Loading model MLP...
Number of parameters: 559111
Start running train at 05-14 03:36:49
Epoch: 0, Time: 0.0134, Loss: 1.9726, TrainAcc: 0.1669, ValAcc: 0.1808, ES: 00/50 | BestVal=0.1808@E0
Epoch: 10, Time: 0.0123, Loss: 0.6978, TrainAcc: 0.7783, ValAcc: 0.6236, ES: 00/50 | BestVal=0.6236@E10
Epoch: 20, Time: 0.0123, Loss: 0.5573, TrainAcc: 0.8282, ValAcc: 0.7066, ES: 00/50 | BestVal=0.7066@E20
Epoch: 30, Time: 0.0059, Loss: 0.4623, TrainAcc: 0.8522, ValAcc: 0.7103, ES: 01/50 | BestVal=0.7214@E29
Epoch: 40, Time: 0.0109, Loss: 0.3314, TrainAcc: 0.8812, ValAcc: 0.7694, ES: 00/50 | BestVal=0.7694@E40
Epoch: 50, Time: 0.0060, Loss: 0.2270, TrainAcc: 0.9243, ValAcc: 0.7399, ES: 10/50 | BestVal=0.7694@E40
Epoch: 60, Time: 0.0049, Loss: 0.2256, TrainAcc: 0.9212, ValAcc: 0.7638, ES: 20/50 | BestVal=0.7694@E40
Epoch: 70, Time: 0.0048, Loss: 0.1104, TrainAcc: 0.9674, ValAcc: 0.7362, ES: 30/50 | BestVal=0.7694@E40
Epoch: 80, Time: 0.0054, Loss: 0.0604, TrainAcc: 0.9877, ValAcc: 0.7565, ES: 40/50 | BestVal=0.7694@E40
Epoch: 90, Time: 0.0048, Loss: 0.0375, TrainAcc: 0.9920, ValAcc: 0.7694, ES: 04/50 | BestVal=0.7712@E86
Epoch: 100, Time: 0.0046, Loss: 0.0159, TrainAcc: 0.9969, ValAcc: 0.7749, ES: 01/50 | BestVal=0.7786@E99
Epoch: 110, Time: 0.0044, Loss: 0.0067, TrainAcc: 1.0000, ValAcc: 0.7768, ES: 04/50 | BestVal=0.7915@E106
Epoch: 120, Time: 0.0044, Loss: 0.0035, TrainAcc: 1.0000, ValAcc: 0.7694, ES: 14/50 | BestVal=0.7915@E106
Epoch: 130, Time: 0.0046, Loss: 0.0021, TrainAcc: 1.0000, ValAcc: 0.7712, ES: 24/50 | BestVal=0.7915@E106
Epoch: 140, Time: 0.0044, Loss: 0.0015, TrainAcc: 1.0000, ValAcc: 0.7675, ES: 34/50 | BestVal=0.7915@E106
Epoch: 150, Time: 0.0046, Loss: 0.0012, TrainAcc: 1.0000, ValAcc: 0.7694, ES: 44/50 | BestVal=0.7915@E106
Early stopped, loading model from epoch-106
Finished running train at 05-14 03:36:50, running time = 1.01s.
[MLP + TA] ValAcc: 0.7915, TestAcc: 0.7232
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 117767
Start running train at 05-14 03:36:53
Epoch: 0, Time: 0.0099, Loss: 1.9942, TrainAcc: 0.2278, ValAcc: 0.1015, ES: 00/50 | BestVal=0.1015@E0
Epoch: 10, Time: 0.0077, Loss: 0.8812, TrainAcc: 0.6940, ValAcc: 0.4170, ES: 00/50 | BestVal=0.4170@E10
Epoch: 20, Time: 0.0077, Loss: 0.8346, TrainAcc: 0.7038, ValAcc: 0.5683, ES: 00/50 | BestVal=0.5683@E20
Epoch: 30, Time: 0.0047, Loss: 0.8137, TrainAcc: 0.7044, ValAcc: 0.6771, ES: 01/50 | BestVal=0.6808@E29
Epoch: 40, Time: 0.0077, Loss: 0.8057, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E40
Epoch: 50, Time: 0.0077, Loss: 0.8024, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E50
Epoch: 60, Time: 0.0046, Loss: 0.8011, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 07/50 | BestVal=0.6863@E53
Epoch: 70, Time: 0.0044, Loss: 0.8005, TrainAcc: 0.7050, ValAcc: 0.6790, ES: 17/50 | BestVal=0.6863@E53
Epoch: 80, Time: 0.0043, Loss: 0.8002, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 07/50 | BestVal=0.6900@E73
Epoch: 90, Time: 0.0075, Loss: 0.8014, TrainAcc: 0.7050, ValAcc: 0.6919, ES: 00/50 | BestVal=0.6919@E90
Epoch: 100, Time: 0.0047, Loss: 0.8006, TrainAcc: 0.7044, ValAcc: 0.6900, ES: 10/50 | BestVal=0.6919@E90
Epoch: 110, Time: 0.0043, Loss: 0.8001, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 20/50 | BestVal=0.6919@E90
Epoch: 120, Time: 0.0046, Loss: 0.7999, TrainAcc: 0.7050, ValAcc: 0.6882, ES: 30/50 | BestVal=0.6919@E90
Epoch: 130, Time: 0.0042, Loss: 0.7998, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 40/50 | BestVal=0.6919@E90
Early stopped, loading model from epoch-90
Finished running train at 05-14 03:36:54, running time = 0.79s.
[RevGAT + P] ValAcc: 0.6919, TestAcc: 0.7103
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Loading model GCN...
Number of parameters: 117767
Start running train at 05-14 03:36:58
Epoch: 0, Time: 0.0142, Loss: 2.3445, TrainAcc: 0.0924, ValAcc: 0.4299, ES: 00/50 | BestVal=0.4299@E0
Epoch: 10, Time: 0.0103, Loss: 0.4689, TrainAcc: 0.8319, ValAcc: 0.4797, ES: 00/50 | BestVal=0.4797@E10
Epoch: 20, Time: 0.0075, Loss: 0.3580, TrainAcc: 0.8701, ValAcc: 0.7472, ES: 01/50 | BestVal=0.7694@E19
Epoch: 30, Time: 0.0076, Loss: 0.2858, TrainAcc: 0.9058, ValAcc: 0.7399, ES: 11/50 | BestVal=0.7694@E19
Epoch: 40, Time: 0.0147, Loss: 0.2575, TrainAcc: 0.9015, ValAcc: 0.8081, ES: 00/50 | BestVal=0.8081@E40
Epoch: 50, Time: 0.0068, Loss: 0.2035, TrainAcc: 0.9317, ValAcc: 0.8137, ES: 02/50 | BestVal=0.8229@E48
Epoch: 60, Time: 0.0065, Loss: 0.1892, TrainAcc: 0.9236, ValAcc: 0.7860, ES: 09/50 | BestVal=0.8358@E51
Epoch: 70, Time: 0.0065, Loss: 0.1603, TrainAcc: 0.9427, ValAcc: 0.7177, ES: 19/50 | BestVal=0.8358@E51
Epoch: 80, Time: 0.0096, Loss: 0.1283, TrainAcc: 0.9600, ValAcc: 0.8432, ES: 00/50 | BestVal=0.8432@E80
Epoch: 90, Time: 0.0062, Loss: 0.1124, TrainAcc: 0.9624, ValAcc: 0.8303, ES: 03/50 | BestVal=0.8469@E87
Epoch: 100, Time: 0.0064, Loss: 0.0905, TrainAcc: 0.9692, ValAcc: 0.8303, ES: 13/50 | BestVal=0.8469@E87
Epoch: 110, Time: 0.0064, Loss: 0.0780, TrainAcc: 0.9729, ValAcc: 0.8210, ES: 23/50 | BestVal=0.8469@E87
Epoch: 120, Time: 0.0065, Loss: 0.2372, TrainAcc: 0.9033, ValAcc: 0.6937, ES: 33/50 | BestVal=0.8469@E87
Epoch: 130, Time: 0.0064, Loss: 0.1543, TrainAcc: 0.9464, ValAcc: 0.8118, ES: 43/50 | BestVal=0.8469@E87
Early stopped, loading model from epoch-87
Finished running train at 05-14 03:36:59, running time = 1.02s.
[GCN + P] ValAcc: 0.8469, TestAcc: 0.8579
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Loading model SAGE...
Number of parameters: 233351
Start running train at 05-14 03:37:03
Epoch: 0, Time: 0.0170, Loss: 1.9632, TrainAcc: 0.2426, ValAcc: 0.4225, ES: 00/50 | BestVal=0.4225@E0
Epoch: 10, Time: 0.0120, Loss: 0.4829, TrainAcc: 0.8245, ValAcc: 0.5756, ES: 05/50 | BestVal=0.6734@E5
Epoch: 20, Time: 0.0085, Loss: 0.3490, TrainAcc: 0.8732, ValAcc: 0.6347, ES: 15/50 | BestVal=0.6734@E5
Epoch: 30, Time: 0.0083, Loss: 0.2389, TrainAcc: 0.9193, ValAcc: 0.7085, ES: 01/50 | BestVal=0.7251@E29
Epoch: 40, Time: 0.0087, Loss: 0.1993, TrainAcc: 0.9298, ValAcc: 0.7528, ES: 02/50 | BestVal=0.7712@E38
Epoch: 50, Time: 0.0078, Loss: 0.1286, TrainAcc: 0.9526, ValAcc: 0.7731, ES: 03/50 | BestVal=0.7897@E47
Epoch: 60, Time: 0.0078, Loss: 0.0810, TrainAcc: 0.9735, ValAcc: 0.8100, ES: 01/50 | BestVal=0.8118@E59
Epoch: 70, Time: 0.0078, Loss: 0.1046, TrainAcc: 0.9637, ValAcc: 0.7749, ES: 08/50 | BestVal=0.8173@E62
Epoch: 80, Time: 0.0078, Loss: 0.0573, TrainAcc: 0.9821, ValAcc: 0.8026, ES: 18/50 | BestVal=0.8173@E62
Epoch: 90, Time: 0.0080, Loss: 0.0428, TrainAcc: 0.9883, ValAcc: 0.8137, ES: 08/50 | BestVal=0.8192@E82
Epoch: 100, Time: 0.0077, Loss: 0.0310, TrainAcc: 0.9908, ValAcc: 0.8210, ES: 02/50 | BestVal=0.8413@E98
Epoch: 110, Time: 0.0078, Loss: 0.0343, TrainAcc: 0.9865, ValAcc: 0.7823, ES: 12/50 | BestVal=0.8413@E98
Epoch: 120, Time: 0.0078, Loss: 0.0325, TrainAcc: 0.9914, ValAcc: 0.8007, ES: 22/50 | BestVal=0.8413@E98
Epoch: 130, Time: 0.0078, Loss: 0.0243, TrainAcc: 0.9920, ValAcc: 0.8229, ES: 32/50 | BestVal=0.8413@E98
Epoch: 140, Time: 0.0080, Loss: 0.0219, TrainAcc: 0.9932, ValAcc: 0.8358, ES: 01/50 | BestVal=0.8413@E139
Epoch: 150, Time: 0.0078, Loss: 0.0230, TrainAcc: 0.9889, ValAcc: 0.8284, ES: 11/50 | BestVal=0.8413@E139
Epoch: 160, Time: 0.0080, Loss: 0.0230, TrainAcc: 0.9889, ValAcc: 0.8395, ES: 06/50 | BestVal=0.8413@E154
Epoch: 170, Time: 0.0082, Loss: 0.0292, TrainAcc: 0.9914, ValAcc: 0.8192, ES: 07/50 | BestVal=0.8432@E163
Epoch: 180, Time: 0.0077, Loss: 0.0204, TrainAcc: 0.9926, ValAcc: 0.8100, ES: 17/50 | BestVal=0.8432@E163
Epoch: 190, Time: 0.0080, Loss: 0.0178, TrainAcc: 0.9938, ValAcc: 0.8229, ES: 27/50 | BestVal=0.8432@E163
Finished running train at 05-14 03:37:04, running time = 1.82s.
[SAGE + P] ValAcc: 0.8450, TestAcc: 0.8358
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Loading model MLP...
Number of parameters: 117767
Start running train at 05-14 03:37:08
Epoch: 0, Time: 0.0097, Loss: 1.9942, TrainAcc: 0.2278, ValAcc: 0.1015, ES: 00/50 | BestVal=0.1015@E0
Epoch: 10, Time: 0.0082, Loss: 0.8812, TrainAcc: 0.6940, ValAcc: 0.4170, ES: 00/50 | BestVal=0.4170@E10
Epoch: 20, Time: 0.0082, Loss: 0.8346, TrainAcc: 0.7038, ValAcc: 0.5683, ES: 00/50 | BestVal=0.5683@E20
Epoch: 30, Time: 0.0051, Loss: 0.8137, TrainAcc: 0.7044, ValAcc: 0.6771, ES: 01/50 | BestVal=0.6808@E29
Epoch: 40, Time: 0.0082, Loss: 0.8057, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E40
Epoch: 50, Time: 0.0077, Loss: 0.8024, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E50
Epoch: 60, Time: 0.0047, Loss: 0.8011, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 07/50 | BestVal=0.6863@E53
Epoch: 70, Time: 0.0045, Loss: 0.8005, TrainAcc: 0.7050, ValAcc: 0.6790, ES: 17/50 | BestVal=0.6863@E53
Epoch: 80, Time: 0.0047, Loss: 0.8002, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 07/50 | BestVal=0.6900@E73
Epoch: 90, Time: 0.0072, Loss: 0.8014, TrainAcc: 0.7050, ValAcc: 0.6919, ES: 00/50 | BestVal=0.6919@E90
Epoch: 100, Time: 0.0046, Loss: 0.8006, TrainAcc: 0.7044, ValAcc: 0.6900, ES: 10/50 | BestVal=0.6919@E90
Epoch: 110, Time: 0.0045, Loss: 0.8001, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 20/50 | BestVal=0.6919@E90
Epoch: 120, Time: 0.0043, Loss: 0.7999, TrainAcc: 0.7050, ValAcc: 0.6882, ES: 30/50 | BestVal=0.6919@E90
Epoch: 130, Time: 0.0043, Loss: 0.7998, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 40/50 | BestVal=0.6919@E90
Early stopped, loading model from epoch-90
Finished running train at 05-14 03:37:09, running time = 0.81s.
[MLP + P] ValAcc: 0.6919, TestAcc: 0.7103
(TA_P) ValAcc: 0.9004, TestAcc: 0.8782
[{'TA': {'val_acc': 0.7915129151291513, 'test_acc': 0.7232472324723247}, 'P': {'val_acc': 0.6918819188191881, 'test_acc': 0.7103321033210332}, 'ensemble': {'val_acc': 0.9003690036900369, 'test_acc': 0.8782287822878229}}]
Running time: 47.46s
An import exception occurred
loaded dataset: cora
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 559111
Start running train at 05-14 03:37:23
Epoch: 0, Time: 0.9870, Loss: 2.0124, TrainAcc: 0.1250, ValAcc: 0.2915, ES: 00/50 | BestVal=0.2915@E0
Epoch: 10, Time: 0.0119, Loss: 0.6092, TrainAcc: 0.8030, ValAcc: 0.7269, ES: 00/50 | BestVal=0.7269@E10
Epoch: 20, Time: 0.0065, Loss: 0.4353, TrainAcc: 0.8633, ValAcc: 0.7749, ES: 02/50 | BestVal=0.7804@E18
Epoch: 30, Time: 0.0065, Loss: 0.2468, TrainAcc: 0.9261, ValAcc: 0.6882, ES: 12/50 | BestVal=0.7804@E18
Epoch: 40, Time: 0.0064, Loss: 0.1109, TrainAcc: 0.9686, ValAcc: 0.6236, ES: 22/50 | BestVal=0.7804@E18
Epoch: 50, Time: 0.0049, Loss: 0.0275, TrainAcc: 0.9963, ValAcc: 0.6882, ES: 32/50 | BestVal=0.7804@E18
Epoch: 60, Time: 0.0049, Loss: 0.0051, TrainAcc: 1.0000, ValAcc: 0.7288, ES: 42/50 | BestVal=0.7804@E18
Early stopped, loading model from epoch-18
Finished running train at 05-14 03:37:25, running time = 1.52s.
[RevGAT + TA] ValAcc: 0.7804, TestAcc: 0.7620
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Loading model GCN...
Number of parameters: 559111
Start running train at 05-14 03:37:29
Epoch: 0, Time: 0.0206, Loss: 2.0078, TrainAcc: 0.2555, ValAcc: 0.4225, ES: 00/50 | BestVal=0.4225@E0
Epoch: 10, Time: 0.0149, Loss: 0.3794, TrainAcc: 0.8633, ValAcc: 0.6476, ES: 00/50 | BestVal=0.6476@E10
Epoch: 20, Time: 0.0149, Loss: 0.3023, TrainAcc: 0.8892, ValAcc: 0.7823, ES: 00/50 | BestVal=0.7823@E20
Epoch: 30, Time: 0.0133, Loss: 0.2453, TrainAcc: 0.9138, ValAcc: 0.8450, ES: 00/50 | BestVal=0.8450@E30
Epoch: 40, Time: 0.0080, Loss: 0.1955, TrainAcc: 0.9267, ValAcc: 0.8708, ES: 01/50 | BestVal=0.8764@E39
Epoch: 50, Time: 0.0072, Loss: 0.1615, TrainAcc: 0.9403, ValAcc: 0.8911, ES: 01/50 | BestVal=0.8967@E49
Epoch: 60, Time: 0.0070, Loss: 0.1455, TrainAcc: 0.9501, ValAcc: 0.8579, ES: 09/50 | BestVal=0.8985@E51
Epoch: 70, Time: 0.0066, Loss: 0.1246, TrainAcc: 0.9544, ValAcc: 0.8764, ES: 19/50 | BestVal=0.8985@E51
Epoch: 80, Time: 0.0063, Loss: 0.0949, TrainAcc: 0.9674, ValAcc: 0.8745, ES: 29/50 | BestVal=0.8985@E51
Epoch: 90, Time: 0.0065, Loss: 0.1051, TrainAcc: 0.9631, ValAcc: 0.8727, ES: 39/50 | BestVal=0.8985@E51
Epoch: 100, Time: 0.0063, Loss: 0.0752, TrainAcc: 0.9741, ValAcc: 0.8708, ES: 49/50 | BestVal=0.8985@E51
Early stopped, loading model from epoch-51
Finished running train at 05-14 03:37:30, running time = 0.96s.
[GCN + TA] ValAcc: 0.8985, TestAcc: 0.8708
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Loading model SAGE...
Number of parameters: 1117063
Start running train at 05-14 03:37:34
Epoch: 0, Time: 0.0420, Loss: 1.9542, TrainAcc: 0.2094, ValAcc: 0.3653, ES: 00/50 | BestVal=0.3653@E0
Epoch: 10, Time: 0.0187, Loss: 0.4238, TrainAcc: 0.8547, ValAcc: 0.7454, ES: 07/50 | BestVal=0.7878@E3
Epoch: 20, Time: 0.0242, Loss: 0.3304, TrainAcc: 0.8775, ValAcc: 0.8321, ES: 00/50 | BestVal=0.8321@E20
Epoch: 30, Time: 0.0155, Loss: 0.2531, TrainAcc: 0.9052, ValAcc: 0.8616, ES: 02/50 | BestVal=0.8653@E28
Epoch: 40, Time: 0.0251, Loss: 0.1826, TrainAcc: 0.9341, ValAcc: 0.8838, ES: 00/50 | BestVal=0.8838@E40
Epoch: 50, Time: 0.0164, Loss: 0.1537, TrainAcc: 0.9458, ValAcc: 0.8801, ES: 06/50 | BestVal=0.8875@E44
Epoch: 60, Time: 0.0164, Loss: 0.1021, TrainAcc: 0.9674, ValAcc: 0.8819, ES: 16/50 | BestVal=0.8875@E44
Epoch: 70, Time: 0.0165, Loss: 0.0703, TrainAcc: 0.9809, ValAcc: 0.8764, ES: 04/50 | BestVal=0.8875@E66
Epoch: 80, Time: 0.0167, Loss: 0.0322, TrainAcc: 0.9938, ValAcc: 0.8727, ES: 14/50 | BestVal=0.8875@E66
Epoch: 90, Time: 0.0168, Loss: 0.0143, TrainAcc: 0.9982, ValAcc: 0.8690, ES: 24/50 | BestVal=0.8875@E66
Epoch: 100, Time: 0.0167, Loss: 0.0061, TrainAcc: 0.9988, ValAcc: 0.8690, ES: 34/50 | BestVal=0.8875@E66
Epoch: 110, Time: 0.0163, Loss: 0.0034, TrainAcc: 0.9994, ValAcc: 0.8764, ES: 44/50 | BestVal=0.8875@E66
Early stopped, loading model from epoch-66
Finished running train at 05-14 03:37:36, running time = 2.24s.
[SAGE + TA] ValAcc: 0.8875, TestAcc: 0.8948
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/cora/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([2708, 4096])
Loading model MLP...
Number of parameters: 559111
Start running train at 05-14 03:37:39
Epoch: 0, Time: 0.0170, Loss: 2.0124, TrainAcc: 0.1250, ValAcc: 0.2915, ES: 00/50 | BestVal=0.2915@E0
Epoch: 10, Time: 0.0126, Loss: 0.6092, TrainAcc: 0.8030, ValAcc: 0.7269, ES: 00/50 | BestVal=0.7269@E10
Epoch: 20, Time: 0.0069, Loss: 0.4353, TrainAcc: 0.8633, ValAcc: 0.7749, ES: 02/50 | BestVal=0.7804@E18
Epoch: 30, Time: 0.0058, Loss: 0.2468, TrainAcc: 0.9261, ValAcc: 0.6882, ES: 12/50 | BestVal=0.7804@E18
Epoch: 40, Time: 0.0058, Loss: 0.1109, TrainAcc: 0.9686, ValAcc: 0.6236, ES: 22/50 | BestVal=0.7804@E18
Epoch: 50, Time: 0.0058, Loss: 0.0275, TrainAcc: 0.9963, ValAcc: 0.6882, ES: 32/50 | BestVal=0.7804@E18
Epoch: 60, Time: 0.0057, Loss: 0.0051, TrainAcc: 1.0000, ValAcc: 0.7288, ES: 42/50 | BestVal=0.7804@E18
Early stopped, loading model from epoch-18
Finished running train at 05-14 03:37:40, running time = 0.54s.
[MLP + TA] ValAcc: 0.7804, TestAcc: 0.7620
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 117767
Start running train at 05-14 03:37:44
Epoch: 0, Time: 0.0097, Loss: 1.9942, TrainAcc: 0.2278, ValAcc: 0.1015, ES: 00/50 | BestVal=0.1015@E0
Epoch: 10, Time: 0.0076, Loss: 0.8812, TrainAcc: 0.6940, ValAcc: 0.4170, ES: 00/50 | BestVal=0.4170@E10
Epoch: 20, Time: 0.0078, Loss: 0.8346, TrainAcc: 0.7038, ValAcc: 0.5683, ES: 00/50 | BestVal=0.5683@E20
Epoch: 30, Time: 0.0050, Loss: 0.8137, TrainAcc: 0.7044, ValAcc: 0.6771, ES: 01/50 | BestVal=0.6808@E29
Epoch: 40, Time: 0.0079, Loss: 0.8057, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E40
Epoch: 50, Time: 0.0075, Loss: 0.8024, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E50
Epoch: 60, Time: 0.0046, Loss: 0.8011, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 07/50 | BestVal=0.6863@E53
Epoch: 70, Time: 0.0047, Loss: 0.8005, TrainAcc: 0.7050, ValAcc: 0.6790, ES: 17/50 | BestVal=0.6863@E53
Epoch: 80, Time: 0.0047, Loss: 0.8002, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 07/50 | BestVal=0.6900@E73
Epoch: 90, Time: 0.0071, Loss: 0.8014, TrainAcc: 0.7050, ValAcc: 0.6919, ES: 00/50 | BestVal=0.6919@E90
Epoch: 100, Time: 0.0045, Loss: 0.8006, TrainAcc: 0.7044, ValAcc: 0.6900, ES: 10/50 | BestVal=0.6919@E90
Epoch: 110, Time: 0.0046, Loss: 0.8001, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 20/50 | BestVal=0.6919@E90
Epoch: 120, Time: 0.0043, Loss: 0.7999, TrainAcc: 0.7050, ValAcc: 0.6882, ES: 30/50 | BestVal=0.6919@E90
Epoch: 130, Time: 0.0043, Loss: 0.7998, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 40/50 | BestVal=0.6919@E90
Early stopped, loading model from epoch-90
Finished running train at 05-14 03:37:44, running time = 0.80s.
[RevGAT + P] ValAcc: 0.6919, TestAcc: 0.7103
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Loading model GCN...
Number of parameters: 117767
Start running train at 05-14 03:37:48
Epoch: 0, Time: 0.0145, Loss: 2.3445, TrainAcc: 0.0924, ValAcc: 0.4280, ES: 00/50 | BestVal=0.4280@E0
Epoch: 10, Time: 0.0103, Loss: 0.4689, TrainAcc: 0.8319, ValAcc: 0.4815, ES: 00/50 | BestVal=0.4815@E10
Epoch: 20, Time: 0.0072, Loss: 0.3580, TrainAcc: 0.8701, ValAcc: 0.7454, ES: 01/50 | BestVal=0.7694@E19
Epoch: 30, Time: 0.0068, Loss: 0.2851, TrainAcc: 0.9064, ValAcc: 0.7269, ES: 11/50 | BestVal=0.7694@E19
Epoch: 40, Time: 0.0097, Loss: 0.2560, TrainAcc: 0.9070, ValAcc: 0.8210, ES: 00/50 | BestVal=0.8210@E40
Epoch: 50, Time: 0.0063, Loss: 0.1929, TrainAcc: 0.9335, ValAcc: 0.8044, ES: 03/50 | BestVal=0.8229@E47
Epoch: 60, Time: 0.0065, Loss: 0.1974, TrainAcc: 0.9286, ValAcc: 0.7583, ES: 13/50 | BestVal=0.8229@E47
Epoch: 70, Time: 0.0067, Loss: 0.1477, TrainAcc: 0.9507, ValAcc: 0.8081, ES: 01/50 | BestVal=0.8266@E69
Epoch: 80, Time: 0.0064, Loss: 0.1933, TrainAcc: 0.9243, ValAcc: 0.8100, ES: 03/50 | BestVal=0.8487@E77
Epoch: 90, Time: 0.0065, Loss: 0.1235, TrainAcc: 0.9569, ValAcc: 0.7085, ES: 13/50 | BestVal=0.8487@E77
Epoch: 100, Time: 0.0064, Loss: 0.1126, TrainAcc: 0.9581, ValAcc: 0.8339, ES: 23/50 | BestVal=0.8487@E77
Epoch: 110, Time: 0.0066, Loss: 0.0857, TrainAcc: 0.9698, ValAcc: 0.8321, ES: 33/50 | BestVal=0.8487@E77
Epoch: 120, Time: 0.0064, Loss: 0.0724, TrainAcc: 0.9772, ValAcc: 0.8247, ES: 43/50 | BestVal=0.8487@E77
Early stopped, loading model from epoch-77
Finished running train at 05-14 03:37:49, running time = 0.95s.
[GCN + P] ValAcc: 0.8487, TestAcc: 0.8469
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Loading model SAGE...
Number of parameters: 233351
Start running train at 05-14 03:37:53
Epoch: 0, Time: 0.0164, Loss: 1.9632, TrainAcc: 0.2426, ValAcc: 0.4225, ES: 00/50 | BestVal=0.4225@E0
Epoch: 10, Time: 0.0112, Loss: 0.4829, TrainAcc: 0.8245, ValAcc: 0.5756, ES: 05/50 | BestVal=0.6734@E5
Epoch: 20, Time: 0.0081, Loss: 0.3490, TrainAcc: 0.8732, ValAcc: 0.6347, ES: 15/50 | BestVal=0.6734@E5
Epoch: 30, Time: 0.0081, Loss: 0.2389, TrainAcc: 0.9193, ValAcc: 0.7085, ES: 01/50 | BestVal=0.7251@E29
Epoch: 40, Time: 0.0077, Loss: 0.1994, TrainAcc: 0.9298, ValAcc: 0.7509, ES: 02/50 | BestVal=0.7712@E38
Epoch: 50, Time: 0.0078, Loss: 0.1281, TrainAcc: 0.9520, ValAcc: 0.7749, ES: 03/50 | BestVal=0.7915@E47
Epoch: 60, Time: 0.0115, Loss: 0.0851, TrainAcc: 0.9711, ValAcc: 0.8137, ES: 00/50 | BestVal=0.8137@E60
Epoch: 70, Time: 0.0078, Loss: 0.0911, TrainAcc: 0.9723, ValAcc: 0.7897, ES: 08/50 | BestVal=0.8173@E62
Epoch: 80, Time: 0.0111, Loss: 0.0511, TrainAcc: 0.9858, ValAcc: 0.7860, ES: 03/50 | BestVal=0.8247@E77
Epoch: 90, Time: 0.0079, Loss: 0.0688, TrainAcc: 0.9778, ValAcc: 0.7897, ES: 13/50 | BestVal=0.8247@E77
Epoch: 100, Time: 0.0077, Loss: 0.0372, TrainAcc: 0.9908, ValAcc: 0.7915, ES: 23/50 | BestVal=0.8247@E77
Epoch: 110, Time: 0.0077, Loss: 0.0283, TrainAcc: 0.9914, ValAcc: 0.7878, ES: 33/50 | BestVal=0.8247@E77
Epoch: 120, Time: 0.0080, Loss: 0.0336, TrainAcc: 0.9895, ValAcc: 0.7565, ES: 43/50 | BestVal=0.8247@E77
Epoch: 130, Time: 0.0079, Loss: 0.0257, TrainAcc: 0.9920, ValAcc: 0.8266, ES: 03/50 | BestVal=0.8321@E127
Epoch: 140, Time: 0.0115, Loss: 0.0207, TrainAcc: 0.9932, ValAcc: 0.8376, ES: 00/50 | BestVal=0.8376@E140
Epoch: 150, Time: 0.0079, Loss: 0.0488, TrainAcc: 0.9840, ValAcc: 0.8247, ES: 05/50 | BestVal=0.8395@E145
Epoch: 160, Time: 0.0080, Loss: 0.4429, TrainAcc: 0.9113, ValAcc: 0.6993, ES: 15/50 | BestVal=0.8395@E145
Epoch: 170, Time: 0.0078, Loss: 0.0955, TrainAcc: 0.9711, ValAcc: 0.5959, ES: 25/50 | BestVal=0.8395@E145
Epoch: 180, Time: 0.0078, Loss: 0.0502, TrainAcc: 0.9883, ValAcc: 0.8026, ES: 35/50 | BestVal=0.8395@E145
Epoch: 190, Time: 0.0077, Loss: 0.0368, TrainAcc: 0.9901, ValAcc: 0.7915, ES: 45/50 | BestVal=0.8395@E145
Early stopped, loading model from epoch-145
Finished running train at 05-14 03:37:54, running time = 1.75s.
[SAGE + P] ValAcc: 0.8395, TestAcc: 0.8266
Loading top-k prediction features ...
Loading topk preds from gpt_preds/cora.csv
Loading model MLP...
Number of parameters: 117767
Start running train at 05-14 03:37:58
Epoch: 0, Time: 0.0094, Loss: 1.9942, TrainAcc: 0.2278, ValAcc: 0.1015, ES: 00/50 | BestVal=0.1015@E0
Epoch: 10, Time: 0.0080, Loss: 0.8812, TrainAcc: 0.6940, ValAcc: 0.4170, ES: 00/50 | BestVal=0.4170@E10
Epoch: 20, Time: 0.0081, Loss: 0.8346, TrainAcc: 0.7038, ValAcc: 0.5683, ES: 00/50 | BestVal=0.5683@E20
Epoch: 30, Time: 0.0054, Loss: 0.8137, TrainAcc: 0.7044, ValAcc: 0.6771, ES: 01/50 | BestVal=0.6808@E29
Epoch: 40, Time: 0.0077, Loss: 0.8057, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E40
Epoch: 50, Time: 0.0098, Loss: 0.8024, TrainAcc: 0.7050, ValAcc: 0.6863, ES: 00/50 | BestVal=0.6863@E50
Epoch: 60, Time: 0.0048, Loss: 0.8011, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 07/50 | BestVal=0.6863@E53
Epoch: 70, Time: 0.0048, Loss: 0.8005, TrainAcc: 0.7050, ValAcc: 0.6790, ES: 17/50 | BestVal=0.6863@E53
Epoch: 80, Time: 0.0043, Loss: 0.8002, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 07/50 | BestVal=0.6900@E73
Epoch: 90, Time: 0.0072, Loss: 0.8014, TrainAcc: 0.7050, ValAcc: 0.6919, ES: 00/50 | BestVal=0.6919@E90
Epoch: 100, Time: 0.0044, Loss: 0.8006, TrainAcc: 0.7044, ValAcc: 0.6900, ES: 10/50 | BestVal=0.6919@E90
Epoch: 110, Time: 0.0044, Loss: 0.8001, TrainAcc: 0.7050, ValAcc: 0.6827, ES: 20/50 | BestVal=0.6919@E90
Epoch: 120, Time: 0.0043, Loss: 0.7999, TrainAcc: 0.7050, ValAcc: 0.6882, ES: 30/50 | BestVal=0.6919@E90
Epoch: 130, Time: 0.0042, Loss: 0.7998, TrainAcc: 0.7050, ValAcc: 0.6845, ES: 40/50 | BestVal=0.6919@E90
Early stopped, loading model from epoch-90
Finished running train at 05-14 03:37:59, running time = 0.80s.
[MLP + P] ValAcc: 0.6919, TestAcc: 0.7103
(TA_P) ValAcc: 0.9096, TestAcc: 0.8893
[{'TA': {'val_acc': 0.7804428044280443, 'test_acc': 0.7619926199261993}, 'P': {'val_acc': 0.6918819188191881, 'test_acc': 0.7103321033210332}, 'ensemble': {'val_acc': 0.9095940959409594, 'test_acc': 0.8892988929889298}}]
Running time: 45.87s
An import exception occurred
loaded dataset: pubmed
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 558595
Start running train at 05-14 03:38:10
Epoch: 0, Time: 1.0138, Loss: 1.1788, TrainAcc: 0.2731, ValAcc: 0.4055, ES: 00/50 | BestVal=0.4055@E0
Epoch: 10, Time: 0.0200, Loss: 0.5155, TrainAcc: 0.7876, ValAcc: 0.7309, ES: 03/50 | BestVal=0.7375@E7
Epoch: 20, Time: 0.0207, Loss: 0.4294, TrainAcc: 0.8330, ValAcc: 0.6949, ES: 13/50 | BestVal=0.7375@E7
Epoch: 30, Time: 0.0183, Loss: 0.3733, TrainAcc: 0.8542, ValAcc: 0.8204, ES: 02/50 | BestVal=0.8237@E28
Epoch: 40, Time: 0.0198, Loss: 0.3318, TrainAcc: 0.8720, ValAcc: 0.8007, ES: 12/50 | BestVal=0.8237@E28
Epoch: 50, Time: 0.0257, Loss: 0.3183, TrainAcc: 0.8760, ValAcc: 0.8384, ES: 00/50 | BestVal=0.8384@E50
Epoch: 60, Time: 0.0240, Loss: 0.2866, TrainAcc: 0.8893, ValAcc: 0.8669, ES: 00/50 | BestVal=0.8669@E60
Epoch: 70, Time: 0.0209, Loss: 0.2826, TrainAcc: 0.8896, ValAcc: 0.8346, ES: 09/50 | BestVal=0.8674@E61
Epoch: 80, Time: 0.0193, Loss: 0.2562, TrainAcc: 0.9014, ValAcc: 0.8696, ES: 01/50 | BestVal=0.8722@E79
Epoch: 90, Time: 0.0188, Loss: 0.2419, TrainAcc: 0.9073, ValAcc: 0.8565, ES: 02/50 | BestVal=0.8732@E88
Epoch: 100, Time: 0.0207, Loss: 0.2394, TrainAcc: 0.9075, ValAcc: 0.8405, ES: 12/50 | BestVal=0.8732@E88
Epoch: 110, Time: 0.0211, Loss: 0.2219, TrainAcc: 0.9170, ValAcc: 0.8724, ES: 05/50 | BestVal=0.8755@E105
Epoch: 120, Time: 0.0199, Loss: 0.2048, TrainAcc: 0.9234, ValAcc: 0.8458, ES: 09/50 | BestVal=0.8785@E111
Epoch: 130, Time: 0.0207, Loss: 0.2657, TrainAcc: 0.8994, ValAcc: 0.7877, ES: 19/50 | BestVal=0.8785@E111
Epoch: 140, Time: 0.0206, Loss: 0.2296, TrainAcc: 0.9123, ValAcc: 0.8719, ES: 29/50 | BestVal=0.8785@E111
Epoch: 150, Time: 0.0272, Loss: 0.1990, TrainAcc: 0.9254, ValAcc: 0.8823, ES: 00/50 | BestVal=0.8823@E150
Epoch: 160, Time: 0.0207, Loss: 0.1855, TrainAcc: 0.9314, ValAcc: 0.8623, ES: 09/50 | BestVal=0.8874@E151
Epoch: 170, Time: 0.0202, Loss: 0.2449, TrainAcc: 0.9075, ValAcc: 0.8610, ES: 19/50 | BestVal=0.8874@E151
Epoch: 180, Time: 0.0206, Loss: 0.1848, TrainAcc: 0.9332, ValAcc: 0.8836, ES: 29/50 | BestVal=0.8874@E151
Epoch: 190, Time: 0.0210, Loss: 0.1682, TrainAcc: 0.9370, ValAcc: 0.8646, ES: 03/50 | BestVal=0.8963@E187
Finished running train at 05-14 03:38:16, running time = 5.32s.
[RevGAT + TA] ValAcc: 0.8963, TestAcc: 0.8938
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Loading model GCN...
Number of parameters: 558595
Start running train at 05-14 03:38:18
Epoch: 0, Time: 0.0625, Loss: 1.4623, TrainAcc: 0.1981, ValAcc: 0.5339, ES: 00/50 | BestVal=0.5339@E0
Epoch: 10, Time: 0.0328, Loss: 0.5658, TrainAcc: 0.7746, ValAcc: 0.6650, ES: 01/50 | BestVal=0.7048@E9
Epoch: 20, Time: 0.0349, Loss: 0.5087, TrainAcc: 0.8047, ValAcc: 0.6137, ES: 11/50 | BestVal=0.7048@E9
Epoch: 30, Time: 0.0421, Loss: 0.4621, TrainAcc: 0.8198, ValAcc: 0.7849, ES: 00/50 | BestVal=0.7849@E30
Epoch: 40, Time: 0.0356, Loss: 0.4300, TrainAcc: 0.8352, ValAcc: 0.7958, ES: 04/50 | BestVal=0.8050@E36
Epoch: 50, Time: 0.0345, Loss: 0.4032, TrainAcc: 0.8469, ValAcc: 0.8103, ES: 08/50 | BestVal=0.8161@E42
Epoch: 60, Time: 0.0333, Loss: 0.3809, TrainAcc: 0.8569, ValAcc: 0.8174, ES: 01/50 | BestVal=0.8242@E59
Epoch: 70, Time: 0.0392, Loss: 0.3894, TrainAcc: 0.8546, ValAcc: 0.8329, ES: 00/50 | BestVal=0.8329@E70
Epoch: 80, Time: 0.0407, Loss: 0.3589, TrainAcc: 0.8658, ValAcc: 0.8435, ES: 00/50 | BestVal=0.8435@E80
Epoch: 90, Time: 0.0349, Loss: 0.3694, TrainAcc: 0.8618, ValAcc: 0.8189, ES: 08/50 | BestVal=0.8506@E82
Epoch: 100, Time: 0.0355, Loss: 0.3388, TrainAcc: 0.8730, ValAcc: 0.6404, ES: 18/50 | BestVal=0.8506@E82
Epoch: 110, Time: 0.0357, Loss: 0.3238, TrainAcc: 0.8778, ValAcc: 0.8258, ES: 05/50 | BestVal=0.8511@E105
Epoch: 120, Time: 0.0361, Loss: 0.3419, TrainAcc: 0.8751, ValAcc: 0.7215, ES: 15/50 | BestVal=0.8511@E105
Epoch: 130, Time: 0.0411, Loss: 0.3249, TrainAcc: 0.8773, ValAcc: 0.8524, ES: 00/50 | BestVal=0.8524@E130
Epoch: 140, Time: 0.0355, Loss: 0.3111, TrainAcc: 0.8817, ValAcc: 0.8400, ES: 10/50 | BestVal=0.8524@E130
Epoch: 150, Time: 0.0368, Loss: 0.3007, TrainAcc: 0.8872, ValAcc: 0.7842, ES: 20/50 | BestVal=0.8524@E130
Epoch: 160, Time: 0.0363, Loss: 0.3523, TrainAcc: 0.8722, ValAcc: 0.8108, ES: 30/50 | BestVal=0.8524@E130
Epoch: 170, Time: 0.0349, Loss: 0.3080, TrainAcc: 0.8850, ValAcc: 0.8067, ES: 40/50 | BestVal=0.8524@E130
Epoch: 180, Time: 0.0356, Loss: 0.3044, TrainAcc: 0.8824, ValAcc: 0.7573, ES: 07/50 | BestVal=0.8544@E173
Epoch: 190, Time: 0.0355, Loss: 0.2833, TrainAcc: 0.8940, ValAcc: 0.8298, ES: 17/50 | BestVal=0.8544@E173
Finished running train at 05-14 03:38:25, running time = 7.33s.
[GCN + TA] ValAcc: 0.8592, TestAcc: 0.8595
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Loading model SAGE...
Number of parameters: 1116035
Start running train at 05-14 03:38:27
Epoch: 0, Time: 0.1873, Loss: 1.1836, TrainAcc: 0.3063, ValAcc: 0.4484, ES: 00/50 | BestVal=0.4484@E0
Epoch: 10, Time: 0.1320, Loss: 0.5595, TrainAcc: 0.7683, ValAcc: 0.6688, ES: 00/50 | BestVal=0.6688@E10
Epoch: 20, Time: 0.1282, Loss: 0.5122, TrainAcc: 0.7954, ValAcc: 0.7568, ES: 00/50 | BestVal=0.7568@E20
Epoch: 30, Time: 0.1328, Loss: 0.4586, TrainAcc: 0.8183, ValAcc: 0.7654, ES: 00/50 | BestVal=0.7654@E30
Epoch: 40, Time: 0.1252, Loss: 0.4132, TrainAcc: 0.8379, ValAcc: 0.8073, ES: 00/50 | BestVal=0.8073@E40
Epoch: 50, Time: 0.1335, Loss: 0.3771, TrainAcc: 0.8506, ValAcc: 0.8088, ES: 00/50 | BestVal=0.8088@E50
Epoch: 60, Time: 0.1252, Loss: 0.3445, TrainAcc: 0.8655, ValAcc: 0.8359, ES: 00/50 | BestVal=0.8359@E60
Epoch: 70, Time: 0.1202, Loss: 0.3198, TrainAcc: 0.8755, ValAcc: 0.8430, ES: 01/50 | BestVal=0.8440@E69
Epoch: 80, Time: 0.1214, Loss: 0.3129, TrainAcc: 0.8817, ValAcc: 0.8554, ES: 03/50 | BestVal=0.8565@E77
Epoch: 90, Time: 0.1203, Loss: 0.2738, TrainAcc: 0.8970, ValAcc: 0.8666, ES: 05/50 | BestVal=0.8679@E85
Epoch: 100, Time: 0.1218, Loss: 0.2567, TrainAcc: 0.9036, ValAcc: 0.8415, ES: 15/50 | BestVal=0.8679@E85
Epoch: 110, Time: 0.1206, Loss: 0.2568, TrainAcc: 0.9014, ValAcc: 0.8608, ES: 25/50 | BestVal=0.8679@E85
Epoch: 120, Time: 0.1228, Loss: 0.2237, TrainAcc: 0.9157, ValAcc: 0.8455, ES: 06/50 | BestVal=0.8717@E114
Epoch: 130, Time: 0.1224, Loss: 0.2249, TrainAcc: 0.9139, ValAcc: 0.7099, ES: 16/50 | BestVal=0.8717@E114
Epoch: 140, Time: 0.1220, Loss: 0.2994, TrainAcc: 0.8850, ValAcc: 0.8577, ES: 26/50 | BestVal=0.8717@E114
Epoch: 150, Time: 0.1202, Loss: 0.2485, TrainAcc: 0.9064, ValAcc: 0.8618, ES: 04/50 | BestVal=0.8740@E146
Epoch: 160, Time: 0.1216, Loss: 0.2207, TrainAcc: 0.9167, ValAcc: 0.8387, ES: 06/50 | BestVal=0.8767@E154
Epoch: 170, Time: 0.1236, Loss: 0.1990, TrainAcc: 0.9253, ValAcc: 0.8435, ES: 16/50 | BestVal=0.8767@E154
Epoch: 180, Time: 0.1187, Loss: 0.1839, TrainAcc: 0.9309, ValAcc: 0.8466, ES: 26/50 | BestVal=0.8767@E154
Epoch: 190, Time: 0.1202, Loss: 0.1920, TrainAcc: 0.9269, ValAcc: 0.8595, ES: 36/50 | BestVal=0.8767@E154
Finished running train at 05-14 03:38:52, running time = 24.61s.
[SAGE + TA] ValAcc: 0.8767, TestAcc: 0.8793
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Alibaba-NLP/gte-Qwen1.5-7B-instruct-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Loading model MLP...
Number of parameters: 558595
Start running train at 05-14 03:38:54
Epoch: 0, Time: 0.0421, Loss: 1.1788, TrainAcc: 0.2731, ValAcc: 0.4055, ES: 00/50 | BestVal=0.4055@E0
Epoch: 10, Time: 0.0204, Loss: 0.5155, TrainAcc: 0.7876, ValAcc: 0.7309, ES: 03/50 | BestVal=0.7375@E7
Epoch: 20, Time: 0.0202, Loss: 0.4294, TrainAcc: 0.8330, ValAcc: 0.6949, ES: 13/50 | BestVal=0.7375@E7
Epoch: 30, Time: 0.0185, Loss: 0.3733, TrainAcc: 0.8542, ValAcc: 0.8204, ES: 02/50 | BestVal=0.8237@E28
Epoch: 40, Time: 0.0201, Loss: 0.3318, TrainAcc: 0.8720, ValAcc: 0.8007, ES: 12/50 | BestVal=0.8237@E28
Epoch: 50, Time: 0.0261, Loss: 0.3183, TrainAcc: 0.8760, ValAcc: 0.8384, ES: 00/50 | BestVal=0.8384@E50
Epoch: 60, Time: 0.0266, Loss: 0.2866, TrainAcc: 0.8893, ValAcc: 0.8669, ES: 00/50 | BestVal=0.8669@E60
Epoch: 70, Time: 0.0203, Loss: 0.2826, TrainAcc: 0.8896, ValAcc: 0.8346, ES: 09/50 | BestVal=0.8674@E61
Epoch: 80, Time: 0.0196, Loss: 0.2562, TrainAcc: 0.9014, ValAcc: 0.8696, ES: 01/50 | BestVal=0.8722@E79
Epoch: 90, Time: 0.0189, Loss: 0.2419, TrainAcc: 0.9073, ValAcc: 0.8565, ES: 02/50 | BestVal=0.8732@E88
Epoch: 100, Time: 0.0214, Loss: 0.2394, TrainAcc: 0.9075, ValAcc: 0.8405, ES: 12/50 | BestVal=0.8732@E88
Epoch: 110, Time: 0.0215, Loss: 0.2219, TrainAcc: 0.9170, ValAcc: 0.8724, ES: 05/50 | BestVal=0.8755@E105
Epoch: 120, Time: 0.0206, Loss: 0.2048, TrainAcc: 0.9234, ValAcc: 0.8458, ES: 09/50 | BestVal=0.8785@E111
Epoch: 130, Time: 0.0202, Loss: 0.2657, TrainAcc: 0.8994, ValAcc: 0.7877, ES: 19/50 | BestVal=0.8785@E111
Epoch: 140, Time: 0.0205, Loss: 0.2296, TrainAcc: 0.9123, ValAcc: 0.8719, ES: 29/50 | BestVal=0.8785@E111
Epoch: 150, Time: 0.0256, Loss: 0.1990, TrainAcc: 0.9254, ValAcc: 0.8823, ES: 00/50 | BestVal=0.8823@E150
Epoch: 160, Time: 0.0215, Loss: 0.1855, TrainAcc: 0.9314, ValAcc: 0.8623, ES: 09/50 | BestVal=0.8874@E151
Epoch: 170, Time: 0.0203, Loss: 0.2449, TrainAcc: 0.9075, ValAcc: 0.8610, ES: 19/50 | BestVal=0.8874@E151
Epoch: 180, Time: 0.0198, Loss: 0.1848, TrainAcc: 0.9332, ValAcc: 0.8836, ES: 29/50 | BestVal=0.8874@E151
Epoch: 190, Time: 0.0215, Loss: 0.1682, TrainAcc: 0.9370, ValAcc: 0.8646, ES: 03/50 | BestVal=0.8963@E187
Finished running train at 05-14 03:38:58, running time = 4.32s.
[MLP + TA] ValAcc: 0.8963, TestAcc: 0.8938
Loading top-k prediction features ...
Loading topk preds from gpt_preds/pubmed.csv
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 83971
Start running train at 05-14 03:39:01
Epoch: 0, Time: 0.0174, Loss: 1.3548, TrainAcc: 0.0407, ValAcc: 0.9343, ES: 00/50 | BestVal=0.9343@E0
Epoch: 10, Time: 0.0161, Loss: 0.2513, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E10
Epoch: 20, Time: 0.0125, Loss: 0.2444, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E20
Epoch: 30, Time: 0.0116, Loss: 0.2426, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E30
Epoch: 40, Time: 0.0115, Loss: 0.2425, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E40
Epoch: 50, Time: 0.0116, Loss: 0.2423, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E50
Epoch: 60, Time: 0.0119, Loss: 0.2422, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E60
Epoch: 70, Time: 0.0119, Loss: 0.2421, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E70
Epoch: 80, Time: 0.0118, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E80
Epoch: 90, Time: 0.0113, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E90
Epoch: 100, Time: 0.0115, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E100
Epoch: 110, Time: 0.0127, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E110
Epoch: 120, Time: 0.0117, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E120
Epoch: 130, Time: 0.0116, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E130
Epoch: 140, Time: 0.0118, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E140
Epoch: 150, Time: 0.0117, Loss: 0.2421, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E150
Epoch: 160, Time: 0.0120, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9358, ES: 00/50 | BestVal=0.9358@E160
Epoch: 170, Time: 0.0092, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 04/50 | BestVal=0.9358@E166
Epoch: 180, Time: 0.0093, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 14/50 | BestVal=0.9358@E166
Epoch: 190, Time: 0.0093, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 24/50 | BestVal=0.9358@E166
Finished running train at 05-14 03:39:03, running time = 2.31s.
[RevGAT + P] ValAcc: 0.9358, TestAcc: 0.9369
Loading top-k prediction features ...
Loading topk preds from gpt_preds/pubmed.csv
Loading model GCN...
Number of parameters: 83971
Start running train at 05-14 03:39:05
Epoch: 0, Time: 0.0386, Loss: 1.2580, TrainAcc: 0.1954, ValAcc: 0.8494, ES: 00/50 | BestVal=0.8494@E0
Epoch: 10, Time: 0.0242, Loss: 0.3007, TrainAcc: 0.8979, ValAcc: 0.5186, ES: 10/50 | BestVal=0.8494@E0
Epoch: 20, Time: 0.0260, Loss: 0.2598, TrainAcc: 0.9142, ValAcc: 0.8681, ES: 00/50 | BestVal=0.8681@E20
Epoch: 30, Time: 0.0259, Loss: 0.2409, TrainAcc: 0.9205, ValAcc: 0.9029, ES: 00/50 | BestVal=0.9029@E30
Epoch: 40, Time: 0.0235, Loss: 0.2293, TrainAcc: 0.9222, ValAcc: 0.9153, ES: 03/50 | BestVal=0.9161@E37
Epoch: 50, Time: 0.0265, Loss: 0.2204, TrainAcc: 0.9264, ValAcc: 0.9163, ES: 00/50 | BestVal=0.9163@E50
Epoch: 60, Time: 0.0235, Loss: 0.2240, TrainAcc: 0.9249, ValAcc: 0.9044, ES: 10/50 | BestVal=0.9163@E50
Epoch: 70, Time: 0.0238, Loss: 0.2164, TrainAcc: 0.9285, ValAcc: 0.9105, ES: 05/50 | BestVal=0.9163@E65
Epoch: 80, Time: 0.0232, Loss: 0.2105, TrainAcc: 0.9313, ValAcc: 0.9128, ES: 15/50 | BestVal=0.9163@E65
Epoch: 90, Time: 0.0236, Loss: 0.2102, TrainAcc: 0.9289, ValAcc: 0.9145, ES: 06/50 | BestVal=0.9191@E84
Epoch: 100, Time: 0.0238, Loss: 0.2428, TrainAcc: 0.9204, ValAcc: 0.9041, ES: 16/50 | BestVal=0.9191@E84
Epoch: 110, Time: 0.0237, Loss: 0.2139, TrainAcc: 0.9287, ValAcc: 0.9120, ES: 26/50 | BestVal=0.9191@E84
Epoch: 120, Time: 0.0235, Loss: 0.2041, TrainAcc: 0.9311, ValAcc: 0.9158, ES: 03/50 | BestVal=0.9191@E117
Epoch: 130, Time: 0.0237, Loss: 0.1952, TrainAcc: 0.9346, ValAcc: 0.9115, ES: 02/50 | BestVal=0.9194@E128
Epoch: 140, Time: 0.0234, Loss: 0.1914, TrainAcc: 0.9365, ValAcc: 0.9183, ES: 08/50 | BestVal=0.9201@E132
Epoch: 150, Time: 0.0236, Loss: 0.2220, TrainAcc: 0.9267, ValAcc: 0.9097, ES: 18/50 | BestVal=0.9201@E132
Epoch: 160, Time: 0.0234, Loss: 0.1948, TrainAcc: 0.9369, ValAcc: 0.9155, ES: 28/50 | BestVal=0.9201@E132
Epoch: 170, Time: 0.0260, Loss: 0.1875, TrainAcc: 0.9384, ValAcc: 0.9237, ES: 00/50 | BestVal=0.9237@E170
Epoch: 180, Time: 0.0235, Loss: 0.1845, TrainAcc: 0.9393, ValAcc: 0.9214, ES: 10/50 | BestVal=0.9237@E170
Epoch: 190, Time: 0.0234, Loss: 0.2432, TrainAcc: 0.9274, ValAcc: 0.8894, ES: 20/50 | BestVal=0.9237@E170
Finished running train at 05-14 03:39:10, running time = 4.87s.
[GCN + P] ValAcc: 0.9237, TestAcc: 0.9255
Loading top-k prediction features ...
Loading topk preds from gpt_preds/pubmed.csv
Loading model SAGE...
Number of parameters: 166275
Start running train at 05-14 03:39:12
Epoch: 0, Time: 0.0526, Loss: 1.2715, TrainAcc: 0.3951, ValAcc: 0.8161, ES: 00/50 | BestVal=0.8161@E0
Epoch: 10, Time: 0.0356, Loss: 0.2293, TrainAcc: 0.9325, ValAcc: 0.9125, ES: 00/50 | BestVal=0.9125@E10
Epoch: 20, Time: 0.0318, Loss: 0.2076, TrainAcc: 0.9342, ValAcc: 0.9328, ES: 02/50 | BestVal=0.9330@E18
Epoch: 30, Time: 0.0359, Loss: 0.1980, TrainAcc: 0.9360, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E30
Epoch: 40, Time: 0.0374, Loss: 0.1923, TrainAcc: 0.9376, ValAcc: 0.9369, ES: 00/50 | BestVal=0.9369@E40
Epoch: 50, Time: 0.0319, Loss: 0.1875, TrainAcc: 0.9387, ValAcc: 0.9356, ES: 08/50 | BestVal=0.9369@E42
Epoch: 60, Time: 0.0327, Loss: 0.1830, TrainAcc: 0.9396, ValAcc: 0.9358, ES: 18/50 | BestVal=0.9369@E42
Epoch: 70, Time: 0.0336, Loss: 0.1781, TrainAcc: 0.9417, ValAcc: 0.9351, ES: 28/50 | BestVal=0.9369@E42
Epoch: 80, Time: 0.0323, Loss: 0.1727, TrainAcc: 0.9431, ValAcc: 0.9330, ES: 38/50 | BestVal=0.9369@E42
Epoch: 90, Time: 0.0320, Loss: 0.1751, TrainAcc: 0.9418, ValAcc: 0.9356, ES: 01/50 | BestVal=0.9371@E89
Epoch: 100, Time: 0.0335, Loss: 0.1673, TrainAcc: 0.9453, ValAcc: 0.9353, ES: 11/50 | BestVal=0.9371@E89
Epoch: 110, Time: 0.0329, Loss: 0.1641, TrainAcc: 0.9462, ValAcc: 0.9351, ES: 21/50 | BestVal=0.9371@E89
Epoch: 120, Time: 0.0324, Loss: 0.1560, TrainAcc: 0.9493, ValAcc: 0.9290, ES: 31/50 | BestVal=0.9371@E89
Epoch: 130, Time: 0.0329, Loss: 0.1618, TrainAcc: 0.9464, ValAcc: 0.9323, ES: 41/50 | BestVal=0.9371@E89
Early stopped, loading model from epoch-89
Finished running train at 05-14 03:39:17, running time = 4.75s.
[SAGE + P] ValAcc: 0.9371, TestAcc: 0.9386
Loading top-k prediction features ...
Loading topk preds from gpt_preds/pubmed.csv
Loading model MLP...
Number of parameters: 83971
Start running train at 05-14 03:39:19
Epoch: 0, Time: 0.0173, Loss: 1.3548, TrainAcc: 0.0407, ValAcc: 0.9343, ES: 00/50 | BestVal=0.9343@E0
Epoch: 10, Time: 0.0160, Loss: 0.2513, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E10
Epoch: 20, Time: 0.0127, Loss: 0.2444, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E20
Epoch: 30, Time: 0.0125, Loss: 0.2426, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E30
Epoch: 40, Time: 0.0114, Loss: 0.2425, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E40
Epoch: 50, Time: 0.0116, Loss: 0.2423, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E50
Epoch: 60, Time: 0.0114, Loss: 0.2422, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E60
Epoch: 70, Time: 0.0114, Loss: 0.2421, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E70
Epoch: 80, Time: 0.0114, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E80
Epoch: 90, Time: 0.0115, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E90
Epoch: 100, Time: 0.0121, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E100
Epoch: 110, Time: 0.0117, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E110
Epoch: 120, Time: 0.0120, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E120
Epoch: 130, Time: 0.0117, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E130
Epoch: 140, Time: 0.0119, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E140
Epoch: 150, Time: 0.0119, Loss: 0.2421, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E150
Epoch: 160, Time: 0.0121, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9358, ES: 00/50 | BestVal=0.9358@E160
Epoch: 170, Time: 0.0089, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 04/50 | BestVal=0.9358@E166
Epoch: 180, Time: 0.0093, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 14/50 | BestVal=0.9358@E166
Epoch: 190, Time: 0.0096, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 24/50 | BestVal=0.9358@E166
Finished running train at 05-14 03:39:22, running time = 2.33s.
[MLP + P] ValAcc: 0.9358, TestAcc: 0.9369
(TA_P) ValAcc: 0.9351, TestAcc: 0.9381
[{'TA': {'val_acc': 0.8962718742074562, 'test_acc': 0.893762677484787}, 'P': {'val_acc': 0.9358356581283287, 'test_acc': 0.9368661257606491}, 'ensemble': {'val_acc': 0.9350748161298503, 'test_acc': 0.9381338742393509}}]
Running time: 78.69s
An import exception occurred
loaded dataset: pubmed
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 558595
Start running train at 05-14 03:39:33
Epoch: 0, Time: 1.0115, Loss: 1.1125, TrainAcc: 0.3672, ValAcc: 0.4180, ES: 00/50 | BestVal=0.4180@E0
Epoch: 10, Time: 0.0179, Loss: 0.3402, TrainAcc: 0.8698, ValAcc: 0.7832, ES: 02/50 | BestVal=0.8354@E8
Epoch: 20, Time: 0.0252, Loss: 0.2845, TrainAcc: 0.8916, ValAcc: 0.8524, ES: 00/50 | BestVal=0.8524@E20
Epoch: 30, Time: 0.0225, Loss: 0.2313, TrainAcc: 0.9161, ValAcc: 0.8940, ES: 00/50 | BestVal=0.8940@E30
Epoch: 40, Time: 0.0233, Loss: 0.1931, TrainAcc: 0.9285, ValAcc: 0.9064, ES: 00/50 | BestVal=0.9064@E40
Epoch: 50, Time: 0.0201, Loss: 0.1590, TrainAcc: 0.9416, ValAcc: 0.9107, ES: 08/50 | BestVal=0.9125@E42
Epoch: 60, Time: 0.0202, Loss: 0.1378, TrainAcc: 0.9520, ValAcc: 0.8958, ES: 18/50 | BestVal=0.9125@E42
Epoch: 70, Time: 0.0198, Loss: 0.1207, TrainAcc: 0.9565, ValAcc: 0.8912, ES: 28/50 | BestVal=0.9125@E42
Epoch: 80, Time: 0.0205, Loss: 0.1162, TrainAcc: 0.9567, ValAcc: 0.9090, ES: 38/50 | BestVal=0.9125@E42
Epoch: 90, Time: 0.0200, Loss: 0.0936, TrainAcc: 0.9684, ValAcc: 0.9062, ES: 48/50 | BestVal=0.9125@E42
Early stopped, loading model from epoch-42
Finished running train at 05-14 03:39:36, running time = 3.04s.
[RevGAT + TA] ValAcc: 0.9125, TestAcc: 0.9158
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Loading model GCN...
Number of parameters: 558595
Start running train at 05-14 03:39:38
Epoch: 0, Time: 0.0586, Loss: 1.5032, TrainAcc: 0.2050, ValAcc: 0.4055, ES: 00/50 | BestVal=0.4055@E0
Epoch: 10, Time: 0.0350, Loss: 0.4672, TrainAcc: 0.8190, ValAcc: 0.6386, ES: 05/50 | BestVal=0.6525@E5
Epoch: 20, Time: 0.0340, Loss: 0.4325, TrainAcc: 0.8323, ValAcc: 0.7974, ES: 02/50 | BestVal=0.8128@E18
Epoch: 30, Time: 0.0399, Loss: 0.4094, TrainAcc: 0.8447, ValAcc: 0.8263, ES: 00/50 | BestVal=0.8263@E30
Epoch: 40, Time: 0.0351, Loss: 0.3842, TrainAcc: 0.8589, ValAcc: 0.8062, ES: 10/50 | BestVal=0.8263@E30
Epoch: 50, Time: 0.0356, Loss: 0.3552, TrainAcc: 0.8701, ValAcc: 0.8209, ES: 20/50 | BestVal=0.8263@E30
Epoch: 60, Time: 0.0399, Loss: 0.3277, TrainAcc: 0.8821, ValAcc: 0.8544, ES: 00/50 | BestVal=0.8544@E60
Epoch: 70, Time: 0.0356, Loss: 0.3025, TrainAcc: 0.8914, ValAcc: 0.8595, ES: 01/50 | BestVal=0.8704@E69
Epoch: 80, Time: 0.0356, Loss: 0.2910, TrainAcc: 0.8943, ValAcc: 0.8220, ES: 03/50 | BestVal=0.8734@E77
Epoch: 90, Time: 0.0347, Loss: 0.2632, TrainAcc: 0.9047, ValAcc: 0.8524, ES: 02/50 | BestVal=0.8821@E88
Epoch: 100, Time: 0.0349, Loss: 0.2538, TrainAcc: 0.9095, ValAcc: 0.8823, ES: 06/50 | BestVal=0.8874@E94
Epoch: 110, Time: 0.0349, Loss: 0.2275, TrainAcc: 0.9194, ValAcc: 0.8544, ES: 16/50 | BestVal=0.8874@E94
Epoch: 120, Time: 0.0364, Loss: 0.2409, TrainAcc: 0.9118, ValAcc: 0.8826, ES: 09/50 | BestVal=0.8922@E111
Epoch: 130, Time: 0.0348, Loss: 0.2123, TrainAcc: 0.9249, ValAcc: 0.8770, ES: 19/50 | BestVal=0.8922@E111
Epoch: 140, Time: 0.0351, Loss: 0.1974, TrainAcc: 0.9316, ValAcc: 0.8598, ES: 29/50 | BestVal=0.8922@E111
Epoch: 150, Time: 0.0353, Loss: 0.2453, TrainAcc: 0.9138, ValAcc: 0.8258, ES: 39/50 | BestVal=0.8922@E111
Epoch: 160, Time: 0.0355, Loss: 0.2049, TrainAcc: 0.9275, ValAcc: 0.8524, ES: 49/50 | BestVal=0.8922@E111
Early stopped, loading model from epoch-111
Finished running train at 05-14 03:39:44, running time = 5.91s.
[GCN + TA] ValAcc: 0.8922, TestAcc: 0.8991
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Loading model SAGE...
Number of parameters: 1116035
Start running train at 05-14 03:39:46
Epoch: 0, Time: 0.1858, Loss: 1.1187, TrainAcc: 0.4085, ValAcc: 0.4666, ES: 00/50 | BestVal=0.4666@E0
Epoch: 10, Time: 0.1215, Loss: 0.4526, TrainAcc: 0.8232, ValAcc: 0.8027, ES: 00/50 | BestVal=0.8027@E10
Epoch: 20, Time: 0.1298, Loss: 0.3919, TrainAcc: 0.8536, ValAcc: 0.8248, ES: 00/50 | BestVal=0.8248@E20
Epoch: 30, Time: 0.1203, Loss: 0.3477, TrainAcc: 0.8677, ValAcc: 0.8425, ES: 03/50 | BestVal=0.8471@E27
Epoch: 40, Time: 0.1204, Loss: 0.2997, TrainAcc: 0.8839, ValAcc: 0.8532, ES: 01/50 | BestVal=0.8534@E39
Epoch: 50, Time: 0.1233, Loss: 0.2522, TrainAcc: 0.9074, ValAcc: 0.8813, ES: 00/50 | BestVal=0.8813@E50
Epoch: 60, Time: 0.1213, Loss: 0.2201, TrainAcc: 0.9185, ValAcc: 0.8953, ES: 04/50 | BestVal=0.8975@E56
Epoch: 70, Time: 0.1183, Loss: 0.1824, TrainAcc: 0.9324, ValAcc: 0.8945, ES: 14/50 | BestVal=0.8975@E56
Epoch: 80, Time: 0.1200, Loss: 0.1484, TrainAcc: 0.9454, ValAcc: 0.8940, ES: 04/50 | BestVal=0.8996@E76
Epoch: 90, Time: 0.1158, Loss: 0.1247, TrainAcc: 0.9564, ValAcc: 0.9067, ES: 01/50 | BestVal=0.9095@E89
Epoch: 100, Time: 0.1157, Loss: 0.1103, TrainAcc: 0.9621, ValAcc: 0.9059, ES: 01/50 | BestVal=0.9105@E99
Epoch: 110, Time: 0.1222, Loss: 0.0887, TrainAcc: 0.9687, ValAcc: 0.9059, ES: 05/50 | BestVal=0.9122@E105
Epoch: 120, Time: 0.1214, Loss: 0.1610, TrainAcc: 0.9385, ValAcc: 0.8927, ES: 15/50 | BestVal=0.9122@E105
Epoch: 130, Time: 0.1213, Loss: 0.0878, TrainAcc: 0.9692, ValAcc: 0.9074, ES: 25/50 | BestVal=0.9122@E105
Epoch: 140, Time: 0.1214, Loss: 0.0594, TrainAcc: 0.9802, ValAcc: 0.8904, ES: 35/50 | BestVal=0.9122@E105
Epoch: 150, Time: 0.1220, Loss: 0.0899, TrainAcc: 0.9728, ValAcc: 0.9031, ES: 45/50 | BestVal=0.9122@E105
Early stopped, loading model from epoch-105
Finished running train at 05-14 03:40:05, running time = 19.14s.
[SAGE + TA] ValAcc: 0.9122, TestAcc: 0.9176
Loading pretrained LM features (title and abstract) ...
LM_emb_path: prt_lm/pubmed/Salesforce/SFR-Embedding-Mistral-seed42-dim4096.emb
Embeddings shape: torch.Size([19717, 4096])
Loading model MLP...
Number of parameters: 558595
Start running train at 05-14 03:40:08
Epoch: 0, Time: 0.0414, Loss: 1.1125, TrainAcc: 0.3672, ValAcc: 0.4180, ES: 00/50 | BestVal=0.4180@E0
Epoch: 10, Time: 0.0198, Loss: 0.3402, TrainAcc: 0.8698, ValAcc: 0.7832, ES: 02/50 | BestVal=0.8354@E8
Epoch: 20, Time: 0.0247, Loss: 0.2845, TrainAcc: 0.8916, ValAcc: 0.8524, ES: 00/50 | BestVal=0.8524@E20
Epoch: 30, Time: 0.0243, Loss: 0.2313, TrainAcc: 0.9161, ValAcc: 0.8940, ES: 00/50 | BestVal=0.8940@E30
Epoch: 40, Time: 0.0238, Loss: 0.1931, TrainAcc: 0.9285, ValAcc: 0.9064, ES: 00/50 | BestVal=0.9064@E40
Epoch: 50, Time: 0.0212, Loss: 0.1590, TrainAcc: 0.9416, ValAcc: 0.9107, ES: 08/50 | BestVal=0.9125@E42
Epoch: 60, Time: 0.0212, Loss: 0.1378, TrainAcc: 0.9520, ValAcc: 0.8958, ES: 18/50 | BestVal=0.9125@E42
Epoch: 70, Time: 0.0198, Loss: 0.1207, TrainAcc: 0.9565, ValAcc: 0.8912, ES: 28/50 | BestVal=0.9125@E42
Epoch: 80, Time: 0.0200, Loss: 0.1162, TrainAcc: 0.9567, ValAcc: 0.9090, ES: 38/50 | BestVal=0.9125@E42
Epoch: 90, Time: 0.0203, Loss: 0.0936, TrainAcc: 0.9684, ValAcc: 0.9062, ES: 48/50 | BestVal=0.9125@E42
Early stopped, loading model from epoch-42
Finished running train at 05-14 03:40:10, running time = 2.09s.
[MLP + TA] ValAcc: 0.9125, TestAcc: 0.9158
Loading top-k prediction features ...
Loading topk preds from gpt_preds/pubmed.csv
Model RevGAT is not supported! Loading MLP ...
Loading model RevGAT...
Number of parameters: 83971
Start running train at 05-14 03:40:12
Epoch: 0, Time: 0.0179, Loss: 1.3548, TrainAcc: 0.0407, ValAcc: 0.9343, ES: 00/50 | BestVal=0.9343@E0
Epoch: 10, Time: 0.0161, Loss: 0.2513, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E10
Epoch: 20, Time: 0.0128, Loss: 0.2444, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E20
Epoch: 30, Time: 0.0125, Loss: 0.2426, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E30
Epoch: 40, Time: 0.0117, Loss: 0.2425, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E40
Epoch: 50, Time: 0.0114, Loss: 0.2423, TrainAcc: 0.9325, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E50
Epoch: 60, Time: 0.0118, Loss: 0.2422, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E60
Epoch: 70, Time: 0.0115, Loss: 0.2421, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E70
Epoch: 80, Time: 0.0115, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E80
Epoch: 90, Time: 0.0115, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E90
Epoch: 100, Time: 0.0116, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E100
Epoch: 110, Time: 0.0119, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E110
Epoch: 120, Time: 0.0117, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E120
Epoch: 130, Time: 0.0113, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E130
Epoch: 140, Time: 0.0117, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E140
Epoch: 150, Time: 0.0118, Loss: 0.2421, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 00/50 | BestVal=0.9356@E150
Epoch: 160, Time: 0.0120, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9358, ES: 00/50 | BestVal=0.9358@E160
Epoch: 170, Time: 0.0093, Loss: 0.2420, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 04/50 | BestVal=0.9358@E166
Epoch: 180, Time: 0.0092, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 14/50 | BestVal=0.9358@E166
Epoch: 190, Time: 0.0093, Loss: 0.2419, TrainAcc: 0.9326, ValAcc: 0.9356, ES: 24/50 | BestVal=0.9358@E166
Finished running train at 05-14 03:40:14, running time = 2.32s.
[RevGAT + P] ValAcc: 0.9358, TestAcc: 0.9369
Loading top-k prediction features ...
Loading topk preds from gpt_preds/pubmed.csv