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nohup_llm-llm_jape.txt
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load arguments: {'training_data': '../../datasets/', 'output': '../../output/results/Paper/eCommerceData/', 'dataset_division': '721_5fold', 'embedding_module': 'JAPE', 'alignment_module': 'sharing', 'search_module': 'greedy', 'dim': 100, 'init': 'normal', 'ent_l2_norm': True, 'rel_l2_norm': True, 'loss_norm': 'L2', 'learning_rate': 0.01, 'optimizer': 'Adagrad', 'max_epoch': 2000, 'batch_size': 5000, 'attr_max_epoch': 200, 'top_attr_threshold': 0.9, 'attr_sim_mat_threshold': 0.95, 'attr_sim_mat_beta': 0.001, 'neg_alpha': 0.1, 'neg_sampling': 'uniform', 'neg_triple_num': 1, 'sub_mat_size': 1000, 'batch_threads_num': 2, 'test_threads_num': 4, 'ordered': True, 'start_valid': 100, 'eval_freq': 10, 'stop_metric': 'hits1', 'eval_metric': 'inner', 'csls': 10, 'top_k': [1, 5, 10, 50], 'is_save': True, 'eval_norm': False}
JAPE
<openea.modules.args.args_hander.ARGs object at 0x7f03a4f99780>
read relation triples: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/rel_triples_1
read relation triples: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/rel_triples_2
read attribute triples: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/attr_triples_1
read attribute triples: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/attr_triples_2
read links: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/721_5fold/1/train_links
read links: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/721_5fold/1/valid_links
read links: ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/721_5fold/1/test_links
Number of rt_dict: 3553
Number of hr_dict: 2618
entity relations dict: 3553
Number of av_dict: 3346
entity attributes dict: 3346
KG statistics:
Number of entities: 3556
Number of relations: 3
Number of attributes: 6
Number of relation triples: 27366
Number of attribute triples: 15798
Number of local relation triples: 27366
Number of local attribute triples: 15798
Number of rt_dict: 3553
Number of hr_dict: 2618
entity relations dict: 3553
Number of av_dict: 3346
entity attributes dict: 3346
KG statistics:
Number of entities: 3556
Number of relations: 3
Number of attributes: 6
Number of relation triples: 27366
Number of attribute triples: 15798
Number of local relation triples: 27366
Number of local attribute triples: 15798
Number of rt_dict: 3553
Number of hr_dict: 2618
entity relations dict: 3553
Number of av_dict: 3346
entity attributes dict: 3346
KG statistics:
Number of entities: 3556
Number of relations: 3
Number of attributes: 6
Number of relation triples: 27366
Number of attribute triples: 15798
Number of local relation triples: 27366
Number of local attribute triples: 15798
Number of rt_dict: 3553
Number of hr_dict: 2618
entity relations dict: 3553
Number of av_dict: 3346
entity attributes dict: 3346
KG statistics:
Number of entities: 3556
Number of relations: 3
Number of attributes: 6
Number of relation triples: 27366
Number of attribute triples: 15798
Number of local relation triples: 27366
Number of local attribute triples: 15798
../../output/results/Paper/eCommerceData/ ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/ ['..', '..', 'datasets', 'Ontologies', 'Paper', 'eCommerceData', 'LLM-LLM'] 721_5fold/1/ JAPE
results output folder: ../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/
Training attribute embeddings:
../../output/results/Paper/eCommerceData/ ../../datasets/Ontologies/Paper/eCommerceData/LLM-LLM/ ['..', '..', 'datasets', 'Ontologies', 'Paper', 'eCommerceData', 'LLM-LLM'] 721_5fold/1/ Attr2Vec
results output folder: ../../output/results/Paper/eCommerceData/Attr2Vec/LLM-LLM/721_5fold/1/20231020224347/
total attributes: 6
selected attributes 5
total attributes: 6
selected attributes 5
total selected attributes 10
total attributes: 6
selected attributes 5
total attributes: 6
selected attributes 5
total selected attributes 10
entity attribute dict 5021
training data of attribute correlations 12124
epoch 1, attribute loss: 5.7900, cost time: 0.3562s
epoch 2, attribute loss: 7.9475, cost time: 0.1917s
epoch 3, attribute loss: 6.5728, cost time: 0.0625s
epoch 4, attribute loss: 7.9420, cost time: 0.2172s
epoch 5, attribute loss: 7.8669, cost time: 0.1251s
epoch 6, attribute loss: 5.4215, cost time: 0.1080s
epoch 7, attribute loss: 5.8475, cost time: 0.0881s
epoch 8, attribute loss: 6.0006, cost time: 0.1277s
epoch 9, attribute loss: 8.1735, cost time: 0.1953s
epoch 10, attribute loss: 7.5570, cost time: 0.1180s
epoch 11, attribute loss: 6.3808, cost time: 0.1024s
epoch 12, attribute loss: 6.3173, cost time: 0.1171s
epoch 13, attribute loss: 6.6981, cost time: 0.1407s
epoch 14, attribute loss: 5.8863, cost time: 0.1758s
epoch 15, attribute loss: 8.1710, cost time: 0.1229s
epoch 16, attribute loss: 9.1848, cost time: 0.0962s
epoch 17, attribute loss: 6.9233, cost time: 0.2196s
epoch 18, attribute loss: 7.9830, cost time: 0.1241s
epoch 19, attribute loss: 7.3891, cost time: 0.1947s
epoch 20, attribute loss: 6.3800, cost time: 0.1313s
epoch 21, attribute loss: 6.1748, cost time: 0.1649s
epoch 22, attribute loss: 5.3873, cost time: 0.1585s
epoch 23, attribute loss: 7.2114, cost time: 0.1520s
epoch 24, attribute loss: 7.1161, cost time: 0.1467s
epoch 25, attribute loss: 6.0239, cost time: 0.1573s
epoch 26, attribute loss: 8.6955, cost time: 0.0867s
epoch 27, attribute loss: 6.6170, cost time: 0.1292s
epoch 28, attribute loss: 6.1202, cost time: 0.1324s
epoch 29, attribute loss: 5.4793, cost time: 0.1799s
epoch 30, attribute loss: 9.0419, cost time: 0.4761s
epoch 31, attribute loss: 7.1628, cost time: 0.1473s
epoch 32, attribute loss: 7.4963, cost time: 0.1536s
epoch 33, attribute loss: 7.1169, cost time: 0.1079s
epoch 34, attribute loss: 6.6390, cost time: 0.1714s
epoch 35, attribute loss: 6.3068, cost time: 0.1359s
epoch 36, attribute loss: 6.2841, cost time: 0.2158s
epoch 37, attribute loss: 7.5882, cost time: 0.1068s
epoch 38, attribute loss: 7.4805, cost time: 0.0599s
epoch 39, attribute loss: 5.5205, cost time: 0.0823s
epoch 40, attribute loss: 6.5960, cost time: 0.1047s
epoch 41, attribute loss: 6.7706, cost time: 0.0909s
epoch 42, attribute loss: 6.8389, cost time: 0.2184s
epoch 43, attribute loss: 10.1247, cost time: 0.1110s
epoch 44, attribute loss: 6.1709, cost time: 0.0850s
epoch 45, attribute loss: 6.9813, cost time: 0.1133s
epoch 46, attribute loss: 5.7309, cost time: 0.1204s
epoch 47, attribute loss: 7.6823, cost time: 0.1975s
epoch 48, attribute loss: 5.8850, cost time: 0.2070s
epoch 49, attribute loss: 4.7093, cost time: 0.1443s
epoch 50, attribute loss: 7.0287, cost time: 0.0653s
epoch 51, attribute loss: 5.6695, cost time: 0.1712s
epoch 52, attribute loss: 7.5506, cost time: 0.1196s
epoch 53, attribute loss: 6.0983, cost time: 0.3285s
epoch 54, attribute loss: 9.1003, cost time: 0.1193s
epoch 55, attribute loss: 5.5471, cost time: 0.0807s
epoch 56, attribute loss: 4.6159, cost time: 0.2171s
epoch 57, attribute loss: 6.2743, cost time: 0.2246s
epoch 58, attribute loss: 6.2398, cost time: 0.1145s
epoch 59, attribute loss: 8.4326, cost time: 0.0906s
epoch 60, attribute loss: 6.4461, cost time: 0.1857s
epoch 61, attribute loss: 5.2215, cost time: 0.1664s
epoch 62, attribute loss: 6.3426, cost time: 0.2198s
epoch 63, attribute loss: 5.8450, cost time: 0.1586s
epoch 64, attribute loss: 6.7010, cost time: 0.1973s
epoch 65, attribute loss: 9.0152, cost time: 0.1606s
epoch 66, attribute loss: 7.9761, cost time: 0.1697s
epoch 67, attribute loss: 5.8971, cost time: 0.1349s
epoch 68, attribute loss: 5.5491, cost time: 0.0678s
epoch 69, attribute loss: 5.9216, cost time: 0.1176s
epoch 70, attribute loss: 7.9946, cost time: 0.1886s
epoch 71, attribute loss: 6.5874, cost time: 0.1166s
epoch 72, attribute loss: 6.6678, cost time: 0.0727s
epoch 73, attribute loss: 4.8362, cost time: 0.0979s
epoch 74, attribute loss: 6.1009, cost time: 0.0950s
epoch 75, attribute loss: 5.1435, cost time: 0.0978s
epoch 76, attribute loss: 8.2222, cost time: 0.1256s
epoch 77, attribute loss: 4.7850, cost time: 0.1327s
epoch 78, attribute loss: 5.9529, cost time: 0.1913s
epoch 79, attribute loss: 4.4885, cost time: 0.0678s
epoch 80, attribute loss: 7.1124, cost time: 0.0839s
epoch 81, attribute loss: 4.7253, cost time: 0.1418s
epoch 82, attribute loss: 8.4447, cost time: 0.1096s
epoch 83, attribute loss: 9.2940, cost time: 0.0488s
epoch 84, attribute loss: 4.3457, cost time: 0.0876s
epoch 85, attribute loss: 6.4346, cost time: 0.1424s
epoch 86, attribute loss: 8.2779, cost time: 0.1246s
epoch 87, attribute loss: 5.3239, cost time: 0.2271s
epoch 88, attribute loss: 7.1738, cost time: 0.0766s
epoch 89, attribute loss: 6.1296, cost time: 0.0781s
epoch 90, attribute loss: 9.4750, cost time: 0.2031s
epoch 91, attribute loss: 3.8143, cost time: 0.1881s
epoch 92, attribute loss: 5.9873, cost time: 0.1897s
epoch 93, attribute loss: 5.4238, cost time: 0.1793s
epoch 94, attribute loss: 7.3043, cost time: 0.0804s
epoch 95, attribute loss: 7.2516, cost time: 0.1270s
epoch 96, attribute loss: 6.7744, cost time: 0.1361s
epoch 97, attribute loss: 8.5355, cost time: 0.1462s
epoch 98, attribute loss: 7.7562, cost time: 0.2473s
epoch 99, attribute loss: 4.5890, cost time: 0.1955s
epoch 100, attribute loss: 7.4877, cost time: 0.0881s
epoch 101, attribute loss: 6.4709, cost time: 0.1675s
epoch 102, attribute loss: 3.8805, cost time: 0.0734s
epoch 103, attribute loss: 6.7280, cost time: 0.1016s
epoch 104, attribute loss: 5.4821, cost time: 0.1287s
epoch 105, attribute loss: 5.7481, cost time: 0.2346s
epoch 106, attribute loss: 6.6577, cost time: 0.4066s
epoch 107, attribute loss: 4.5366, cost time: 0.1479s
epoch 108, attribute loss: 5.4583, cost time: 0.3174s
epoch 109, attribute loss: 4.2447, cost time: 0.0974s
epoch 110, attribute loss: 3.7619, cost time: 0.1959s
epoch 111, attribute loss: 9.7280, cost time: 0.1744s
epoch 112, attribute loss: 7.0473, cost time: 0.2443s
epoch 113, attribute loss: 6.6796, cost time: 0.1134s
epoch 114, attribute loss: 6.0581, cost time: 0.2371s
epoch 115, attribute loss: 5.9921, cost time: 0.1423s
epoch 116, attribute loss: 5.7160, cost time: 0.1340s
epoch 117, attribute loss: 6.5281, cost time: 0.1132s
epoch 118, attribute loss: 6.4946, cost time: 0.1038s
epoch 119, attribute loss: 5.3081, cost time: 0.1444s
epoch 120, attribute loss: 5.8870, cost time: 0.1647s
epoch 121, attribute loss: 8.6463, cost time: 0.0989s
epoch 122, attribute loss: 5.4217, cost time: 0.2299s
epoch 123, attribute loss: 7.0498, cost time: 0.2155s
epoch 124, attribute loss: 7.7564, cost time: 0.0831s
epoch 125, attribute loss: 5.3807, cost time: 0.1462s
epoch 126, attribute loss: 7.1643, cost time: 0.1421s
epoch 127, attribute loss: 4.7790, cost time: 0.2124s
epoch 128, attribute loss: 6.3828, cost time: 0.1210s
epoch 129, attribute loss: 6.5954, cost time: 0.0902s
epoch 130, attribute loss: 8.0117, cost time: 0.1094s
epoch 131, attribute loss: 5.2019, cost time: 0.2043s
epoch 132, attribute loss: 5.7948, cost time: 0.2695s
epoch 133, attribute loss: 7.0493, cost time: 0.1183s
epoch 134, attribute loss: 5.7240, cost time: 0.2032s
epoch 135, attribute loss: 7.3797, cost time: 0.0964s
epoch 136, attribute loss: 6.3329, cost time: 0.1276s
epoch 137, attribute loss: 5.9204, cost time: 0.1565s
epoch 138, attribute loss: 6.4976, cost time: 0.2730s
epoch 139, attribute loss: 7.0366, cost time: 0.3111s
epoch 140, attribute loss: 4.3462, cost time: 0.1940s
epoch 141, attribute loss: 6.8498, cost time: 0.1739s
epoch 142, attribute loss: 5.2703, cost time: 0.1896s
epoch 143, attribute loss: 5.2546, cost time: 0.1024s
epoch 144, attribute loss: 4.6401, cost time: 0.1840s
epoch 145, attribute loss: 6.2867, cost time: 0.1379s
epoch 146, attribute loss: 6.1284, cost time: 0.1717s
epoch 147, attribute loss: 7.6213, cost time: 0.0717s
epoch 148, attribute loss: 6.3352, cost time: 0.1932s
epoch 149, attribute loss: 5.0551, cost time: 0.2590s
epoch 150, attribute loss: 7.1710, cost time: 0.1416s
epoch 151, attribute loss: 6.2766, cost time: 0.1194s
epoch 152, attribute loss: 6.6469, cost time: 0.2464s
epoch 153, attribute loss: 6.4206, cost time: 0.1718s
epoch 154, attribute loss: 7.0552, cost time: 0.1276s
epoch 155, attribute loss: 6.4024, cost time: 0.2836s
epoch 156, attribute loss: 4.8532, cost time: 0.2844s
epoch 157, attribute loss: 3.2432, cost time: 0.0644s
epoch 158, attribute loss: 8.9327, cost time: 0.1203s
epoch 159, attribute loss: 7.1151, cost time: 0.2666s
epoch 160, attribute loss: 6.0112, cost time: 0.0996s
epoch 161, attribute loss: 7.3372, cost time: 0.2692s
epoch 162, attribute loss: 5.8101, cost time: 0.2407s
epoch 163, attribute loss: 8.5144, cost time: 0.2391s
epoch 164, attribute loss: 5.5657, cost time: 0.5874s
epoch 165, attribute loss: 3.8295, cost time: 0.1260s
epoch 166, attribute loss: 4.8832, cost time: 0.1897s
epoch 167, attribute loss: 6.9472, cost time: 0.1043s
epoch 168, attribute loss: 5.4293, cost time: 0.1264s
epoch 169, attribute loss: 7.4608, cost time: 0.1065s
epoch 170, attribute loss: 5.4149, cost time: 0.1334s
epoch 171, attribute loss: 4.5414, cost time: 0.1355s
epoch 172, attribute loss: 5.5256, cost time: 0.1325s
epoch 173, attribute loss: 6.2714, cost time: 0.1080s
epoch 174, attribute loss: 6.1627, cost time: 0.1451s
epoch 175, attribute loss: 5.4764, cost time: 0.1527s
epoch 176, attribute loss: 6.6874, cost time: 0.1633s
epoch 177, attribute loss: 5.8181, cost time: 0.1437s
epoch 178, attribute loss: 7.3623, cost time: 0.2298s
epoch 179, attribute loss: 7.5059, cost time: 0.1796s
epoch 180, attribute loss: 5.7826, cost time: 0.1953s
epoch 181, attribute loss: 6.5913, cost time: 0.1203s
epoch 182, attribute loss: 6.1200, cost time: 0.1078s
epoch 183, attribute loss: 6.7637, cost time: 0.1554s
epoch 184, attribute loss: 7.4978, cost time: 0.1682s
epoch 185, attribute loss: 6.7464, cost time: 0.1614s
epoch 186, attribute loss: 5.2528, cost time: 0.2324s
epoch 187, attribute loss: 5.4952, cost time: 0.1095s
epoch 188, attribute loss: 4.6214, cost time: 0.1446s
epoch 189, attribute loss: 6.7447, cost time: 0.2053s
epoch 190, attribute loss: 6.0938, cost time: 0.1521s
epoch 191, attribute loss: 4.4543, cost time: 0.0857s
epoch 192, attribute loss: 5.2631, cost time: 0.0837s
epoch 193, attribute loss: 4.7541, cost time: 0.1431s
epoch 194, attribute loss: 5.5900, cost time: 0.0953s
epoch 195, attribute loss: 3.6522, cost time: 0.2396s
epoch 196, attribute loss: 5.3964, cost time: 0.3153s
epoch 197, attribute loss: 7.5655, cost time: 0.2551s
epoch 198, attribute loss: 5.3163, cost time: 0.1138s
epoch 199, attribute loss: 5.0016, cost time: 0.1693s
epoch 200, attribute loss: 7.8958, cost time: 0.1165s
get entity embeddings from attributes
cost time: 6.0271s
Training attributes ends. Total time = 53.807 s.
Joint training:
epoch 1, avg. triple loss: 2.1126, cost time: 4.0433s
epoch 1, sim loss: 1.0000, cost time: 0.5269s
epoch 2, avg. triple loss: 1.4727, cost time: 3.9333s
epoch 2, sim loss: 1.0000, cost time: 0.0749s
epoch 3, avg. triple loss: 1.2140, cost time: 3.0893s
epoch 3, sim loss: 1.0000, cost time: 0.0994s
epoch 4, avg. triple loss: 1.0699, cost time: 3.9936s
epoch 4, sim loss: 1.0000, cost time: 0.1208s
epoch 5, avg. triple loss: 0.9761, cost time: 3.3032s
epoch 5, sim loss: 1.0000, cost time: 0.0632s
epoch 6, avg. triple loss: 0.9074, cost time: 3.5225s
epoch 6, sim loss: 1.0000, cost time: 0.1298s
epoch 7, avg. triple loss: 0.8538, cost time: 3.9427s
epoch 7, sim loss: 1.0000, cost time: 0.0567s
epoch 8, avg. triple loss: 0.8071, cost time: 3.4628s
epoch 8, sim loss: 1.0000, cost time: 0.0733s
epoch 9, avg. triple loss: 0.7657, cost time: 3.3954s
epoch 9, sim loss: 1.0000, cost time: 0.0479s
epoch 10, avg. triple loss: 0.7262, cost time: 3.6207s
epoch 10, sim loss: 1.0000, cost time: 0.1996s
epoch 11, avg. triple loss: 0.6874, cost time: 3.4013s
epoch 11, sim loss: 1.0000, cost time: 0.0576s
epoch 12, avg. triple loss: 0.6484, cost time: 3.4039s
epoch 12, sim loss: 1.0000, cost time: 0.1341s
epoch 13, avg. triple loss: 0.6081, cost time: 4.8010s
epoch 13, sim loss: 1.0000, cost time: 0.0937s
epoch 14, avg. triple loss: 0.5677, cost time: 2.7976s
epoch 14, sim loss: 1.0000, cost time: 0.0853s
epoch 15, avg. triple loss: 0.5268, cost time: 3.5362s
epoch 15, sim loss: 1.0000, cost time: 0.1625s
epoch 16, avg. triple loss: 0.4854, cost time: 2.8463s
epoch 16, sim loss: 1.0000, cost time: 0.0234s
epoch 17, avg. triple loss: 0.4450, cost time: 3.4419s
epoch 17, sim loss: 1.0000, cost time: 0.1340s
epoch 18, avg. triple loss: 0.4052, cost time: 3.3737s
epoch 18, sim loss: 1.0000, cost time: 0.0203s
epoch 19, avg. triple loss: 0.3672, cost time: 3.8984s
epoch 19, sim loss: 1.0000, cost time: 0.0856s
epoch 20, avg. triple loss: 0.3308, cost time: 3.7604s
epoch 20, sim loss: 1.0000, cost time: 0.0216s
epoch 21, avg. triple loss: 0.2969, cost time: 2.9924s
epoch 21, sim loss: 1.0000, cost time: 0.1309s
epoch 22, avg. triple loss: 0.2652, cost time: 3.8765s
epoch 22, sim loss: 1.0000, cost time: 0.0614s
epoch 23, avg. triple loss: 0.2355, cost time: 2.9596s
epoch 23, sim loss: 1.0000, cost time: 0.2247s
epoch 24, avg. triple loss: 0.2086, cost time: 2.5622s
epoch 24, sim loss: 1.0000, cost time: 0.1935s
epoch 25, avg. triple loss: 0.1840, cost time: 4.3181s
epoch 25, sim loss: 1.0000, cost time: 0.1265s
epoch 26, avg. triple loss: 0.1613, cost time: 4.2263s
epoch 26, sim loss: 1.0000, cost time: 0.1048s
epoch 27, avg. triple loss: 0.1407, cost time: 3.3035s
epoch 27, sim loss: 1.0000, cost time: 0.1062s
epoch 28, avg. triple loss: 0.1221, cost time: 3.7923s
epoch 28, sim loss: 1.0000, cost time: 0.0649s
epoch 29, avg. triple loss: 0.1047, cost time: 2.3922s
epoch 29, sim loss: 1.0000, cost time: 0.0316s
epoch 30, avg. triple loss: 0.0901, cost time: 3.1576s
epoch 30, sim loss: 1.0000, cost time: 0.0656s
epoch 31, avg. triple loss: 0.0766, cost time: 3.1999s
epoch 31, sim loss: 1.0000, cost time: 0.0332s
epoch 32, avg. triple loss: 0.0637, cost time: 3.6237s
epoch 32, sim loss: 1.0000, cost time: 0.0597s
epoch 33, avg. triple loss: 0.0531, cost time: 3.1257s
epoch 33, sim loss: 1.0000, cost time: 0.0705s
epoch 34, avg. triple loss: 0.0416, cost time: 4.3923s
epoch 34, sim loss: 1.0000, cost time: 0.0516s
epoch 35, avg. triple loss: 0.0334, cost time: 2.7401s
epoch 35, sim loss: 1.0000, cost time: 0.0919s
epoch 36, avg. triple loss: 0.0248, cost time: 2.7034s
epoch 36, sim loss: 1.0000, cost time: 0.0395s
epoch 37, avg. triple loss: 0.0176, cost time: 2.8003s
epoch 37, sim loss: 1.0000, cost time: 0.0502s
epoch 38, avg. triple loss: 0.0103, cost time: 2.7574s
epoch 38, sim loss: 1.0000, cost time: 0.0581s
epoch 39, avg. triple loss: 0.0041, cost time: 3.7923s
epoch 39, sim loss: 1.0000, cost time: 0.0748s
epoch 40, avg. triple loss: -0.0016, cost time: 2.4717s
epoch 40, sim loss: 1.0000, cost time: 0.1357s
epoch 41, avg. triple loss: -0.0064, cost time: 3.2827s
epoch 41, sim loss: 1.0000, cost time: 0.0957s
epoch 42, avg. triple loss: -0.0117, cost time: 4.1136s
epoch 42, sim loss: 1.0000, cost time: 0.0546s
epoch 43, avg. triple loss: -0.0166, cost time: 3.3892s
epoch 43, sim loss: 1.0000, cost time: 0.0603s
epoch 44, avg. triple loss: -0.0194, cost time: 3.1877s
epoch 44, sim loss: 1.0000, cost time: 0.0628s
epoch 45, avg. triple loss: -0.0242, cost time: 4.0007s
epoch 45, sim loss: 1.0000, cost time: 0.1135s
epoch 46, avg. triple loss: -0.0271, cost time: 2.4432s
epoch 46, sim loss: 1.0000, cost time: 0.2040s
epoch 47, avg. triple loss: -0.0300, cost time: 2.5166s
epoch 47, sim loss: 1.0000, cost time: 0.0672s
epoch 48, avg. triple loss: -0.0332, cost time: 2.6457s
epoch 48, sim loss: 1.0000, cost time: 0.0548s
epoch 49, avg. triple loss: -0.0362, cost time: 4.0447s
epoch 49, sim loss: 1.0000, cost time: 0.0847s
epoch 50, avg. triple loss: -0.0384, cost time: 3.1290s
epoch 50, sim loss: 1.0000, cost time: 0.0461s
epoch 51, avg. triple loss: -0.0408, cost time: 2.3485s
epoch 51, sim loss: 1.0000, cost time: 0.0325s
epoch 52, avg. triple loss: -0.0430, cost time: 3.3964s
epoch 52, sim loss: 1.0000, cost time: 0.1891s
epoch 53, avg. triple loss: -0.0454, cost time: 3.5919s
epoch 53, sim loss: 1.0000, cost time: 0.0773s
epoch 54, avg. triple loss: -0.0465, cost time: 2.0086s
epoch 54, sim loss: 1.0000, cost time: 0.0432s
epoch 55, avg. triple loss: -0.0478, cost time: 4.0791s
epoch 55, sim loss: 1.0000, cost time: 0.0702s
epoch 56, avg. triple loss: -0.0499, cost time: 2.7799s
epoch 56, sim loss: 1.0000, cost time: 0.0473s
epoch 57, avg. triple loss: -0.0509, cost time: 2.5952s
epoch 57, sim loss: 1.0000, cost time: 0.2193s
epoch 58, avg. triple loss: -0.0519, cost time: 2.9802s
epoch 58, sim loss: 1.0000, cost time: 0.1978s
epoch 59, avg. triple loss: -0.0542, cost time: 2.8507s
epoch 59, sim loss: 1.0000, cost time: 0.0586s
epoch 60, avg. triple loss: -0.0553, cost time: 3.7259s
epoch 60, sim loss: 1.0000, cost time: 0.0966s
epoch 61, avg. triple loss: -0.0557, cost time: 2.9794s
epoch 61, sim loss: 1.0000, cost time: 0.0457s
epoch 62, avg. triple loss: -0.0574, cost time: 2.6004s
epoch 62, sim loss: 1.0000, cost time: 0.0629s
epoch 63, avg. triple loss: -0.0578, cost time: 3.0640s
epoch 63, sim loss: 1.0000, cost time: 0.0355s
epoch 64, avg. triple loss: -0.0592, cost time: 2.8083s
epoch 64, sim loss: 1.0000, cost time: 0.0379s
epoch 65, avg. triple loss: -0.0599, cost time: 3.0627s
epoch 65, sim loss: 1.0000, cost time: 0.0704s
epoch 66, avg. triple loss: -0.0605, cost time: 2.9913s
epoch 66, sim loss: 1.0000, cost time: 0.0728s
epoch 67, avg. triple loss: -0.0612, cost time: 2.7442s
epoch 67, sim loss: 1.0000, cost time: 0.0740s
epoch 68, avg. triple loss: -0.0617, cost time: 2.1511s
epoch 68, sim loss: 1.0000, cost time: 0.0385s
epoch 69, avg. triple loss: -0.0624, cost time: 3.6484s
epoch 69, sim loss: 1.0000, cost time: 0.1279s
epoch 70, avg. triple loss: -0.0638, cost time: 2.8868s
epoch 70, sim loss: 1.0000, cost time: 0.0492s
epoch 71, avg. triple loss: -0.0639, cost time: 2.0872s
epoch 71, sim loss: 1.0000, cost time: 0.0494s
epoch 72, avg. triple loss: -0.0649, cost time: 2.7132s
epoch 72, sim loss: 1.0000, cost time: 0.0632s
epoch 73, avg. triple loss: -0.0653, cost time: 3.5012s
epoch 73, sim loss: 1.0000, cost time: 0.1073s
epoch 74, avg. triple loss: -0.0660, cost time: 3.6516s
epoch 74, sim loss: 1.0000, cost time: 0.0339s
epoch 75, avg. triple loss: -0.0661, cost time: 2.9631s
epoch 75, sim loss: 1.0000, cost time: 0.0287s
epoch 76, avg. triple loss: -0.0665, cost time: 2.8547s
epoch 76, sim loss: 1.0000, cost time: 0.0559s
epoch 77, avg. triple loss: -0.0673, cost time: 2.6771s
epoch 77, sim loss: 1.0000, cost time: 0.0262s
epoch 78, avg. triple loss: -0.0679, cost time: 2.9334s
epoch 78, sim loss: 1.0000, cost time: 0.1890s
epoch 79, avg. triple loss: -0.0680, cost time: 2.5252s
epoch 79, sim loss: 1.0000, cost time: 0.0320s
epoch 80, avg. triple loss: -0.0686, cost time: 2.9189s
epoch 80, sim loss: 1.0000, cost time: 0.0525s
epoch 81, avg. triple loss: -0.0686, cost time: 3.5033s
epoch 81, sim loss: 1.0000, cost time: 0.0697s
epoch 82, avg. triple loss: -0.0692, cost time: 2.7184s
epoch 82, sim loss: 1.0000, cost time: 0.0808s
epoch 83, avg. triple loss: -0.0697, cost time: 2.9690s
epoch 83, sim loss: 1.0000, cost time: 0.0544s
epoch 84, avg. triple loss: -0.0694, cost time: 2.7903s
epoch 84, sim loss: 1.0000, cost time: 0.0330s
epoch 85, avg. triple loss: -0.0701, cost time: 2.9860s
epoch 85, sim loss: 1.0000, cost time: 0.0467s
epoch 86, avg. triple loss: -0.0697, cost time: 2.9829s
epoch 86, sim loss: 1.0000, cost time: 0.0538s
epoch 87, avg. triple loss: -0.0708, cost time: 3.4417s
epoch 87, sim loss: 1.0000, cost time: 0.0485s
epoch 88, avg. triple loss: -0.0710, cost time: 4.0342s
epoch 88, sim loss: 1.0000, cost time: 0.1138s
epoch 89, avg. triple loss: -0.0715, cost time: 2.8082s
epoch 89, sim loss: 1.0000, cost time: 0.0650s
epoch 90, avg. triple loss: -0.0716, cost time: 3.0996s
epoch 90, sim loss: 1.0000, cost time: 0.0487s
epoch 91, avg. triple loss: -0.0720, cost time: 4.2945s
epoch 91, sim loss: 1.0000, cost time: 0.0932s
epoch 92, avg. triple loss: -0.0722, cost time: 2.5032s
epoch 92, sim loss: 1.0000, cost time: 0.0689s
epoch 93, avg. triple loss: -0.0728, cost time: 3.0927s
epoch 93, sim loss: 1.0000, cost time: 0.0602s
epoch 94, avg. triple loss: -0.0721, cost time: 2.7439s
epoch 94, sim loss: 1.0000, cost time: 0.1341s
epoch 95, avg. triple loss: -0.0725, cost time: 2.9113s
epoch 95, sim loss: 1.0000, cost time: 0.0452s
epoch 96, avg. triple loss: -0.0727, cost time: 2.6923s
epoch 96, sim loss: 1.0000, cost time: 0.0229s
epoch 97, avg. triple loss: -0.0731, cost time: 3.1851s
epoch 97, sim loss: 1.0000, cost time: 0.0740s
epoch 98, avg. triple loss: -0.0735, cost time: 2.6964s
epoch 98, sim loss: 1.0000, cost time: 0.0792s
epoch 99, avg. triple loss: -0.0734, cost time: 3.0055s
epoch 99, sim loss: 1.0000, cost time: 0.0586s
epoch 100, avg. triple loss: -0.0726, cost time: 2.3111s
epoch 100, sim loss: 1.0000, cost time: 0.0869s
quick results: hits@[1, 5, 10, 50] = [21.91 36.236 42.978 65.73 ]%, time = 1.447 s
epoch 101, avg. triple loss: -0.0733, cost time: 2.9018s
epoch 101, sim loss: 1.0000, cost time: 0.1270s
epoch 102, avg. triple loss: -0.0733, cost time: 2.9455s
epoch 102, sim loss: 1.0000, cost time: 0.0658s
epoch 103, avg. triple loss: -0.0743, cost time: 3.2242s
epoch 103, sim loss: 1.0000, cost time: 0.0396s
epoch 104, avg. triple loss: -0.0741, cost time: 2.7565s
epoch 104, sim loss: 1.0000, cost time: 0.0298s
epoch 105, avg. triple loss: -0.0743, cost time: 2.4141s
epoch 105, sim loss: 1.0000, cost time: 0.0655s
epoch 106, avg. triple loss: -0.0747, cost time: 3.3837s
epoch 106, sim loss: 1.0000, cost time: 0.0611s
epoch 107, avg. triple loss: -0.0742, cost time: 3.1750s
epoch 107, sim loss: 1.0000, cost time: 0.0614s
epoch 108, avg. triple loss: -0.0746, cost time: 3.3296s
epoch 108, sim loss: 1.0000, cost time: 0.0801s
epoch 109, avg. triple loss: -0.0746, cost time: 2.8702s
epoch 109, sim loss: 1.0000, cost time: 0.1267s
epoch 110, avg. triple loss: -0.0751, cost time: 2.3072s
epoch 110, sim loss: 1.0000, cost time: 0.0802s
quick results: hits@[1, 5, 10, 50] = [22.191 37.36 44.101 66.854]%, time = 1.145 s
epoch 111, avg. triple loss: -0.0749, cost time: 2.6399s
epoch 111, sim loss: 1.0000, cost time: 0.0587s
epoch 112, avg. triple loss: -0.0751, cost time: 2.8848s
epoch 112, sim loss: 1.0000, cost time: 0.0385s
epoch 113, avg. triple loss: -0.0754, cost time: 2.9553s
epoch 113, sim loss: 1.0000, cost time: 0.0370s
epoch 114, avg. triple loss: -0.0751, cost time: 3.0990s
epoch 114, sim loss: 1.0000, cost time: 0.0339s
epoch 115, avg. triple loss: -0.0754, cost time: 3.0842s
epoch 115, sim loss: 1.0000, cost time: 0.0589s
epoch 116, avg. triple loss: -0.0754, cost time: 2.8015s
epoch 116, sim loss: 1.0000, cost time: 0.0878s
epoch 117, avg. triple loss: -0.0755, cost time: 2.3214s
epoch 117, sim loss: 1.0000, cost time: 0.0262s
epoch 118, avg. triple loss: -0.0756, cost time: 2.0665s
epoch 118, sim loss: 1.0000, cost time: 0.0705s
epoch 119, avg. triple loss: -0.0760, cost time: 2.4269s
epoch 119, sim loss: 1.0000, cost time: 0.0677s
epoch 120, avg. triple loss: -0.0759, cost time: 2.7709s
epoch 120, sim loss: 1.0000, cost time: 0.0469s
quick results: hits@[1, 5, 10, 50] = [21.348 37.079 44.663 65.73 ]%, time = 0.972 s
epoch 121, avg. triple loss: -0.0760, cost time: 2.2070s
epoch 121, sim loss: 1.0000, cost time: 0.1112s
epoch 122, avg. triple loss: -0.0767, cost time: 2.4940s
epoch 122, sim loss: 1.0000, cost time: 0.0284s
epoch 123, avg. triple loss: -0.0757, cost time: 2.3747s
epoch 123, sim loss: 1.0000, cost time: 0.1412s
epoch 124, avg. triple loss: -0.0765, cost time: 2.2865s
epoch 124, sim loss: 1.0000, cost time: 0.0638s
epoch 125, avg. triple loss: -0.0762, cost time: 2.7028s
epoch 125, sim loss: 1.0000, cost time: 0.0377s
epoch 126, avg. triple loss: -0.0767, cost time: 2.4512s
epoch 126, sim loss: 1.0000, cost time: 0.0414s
epoch 127, avg. triple loss: -0.0761, cost time: 2.1618s
epoch 127, sim loss: 1.0000, cost time: 0.0376s
epoch 128, avg. triple loss: -0.0766, cost time: 2.1777s
epoch 128, sim loss: 1.0000, cost time: 0.0374s
epoch 129, avg. triple loss: -0.0770, cost time: 2.3326s
epoch 129, sim loss: 1.0000, cost time: 0.0869s
epoch 130, avg. triple loss: -0.0765, cost time: 2.0517s
epoch 130, sim loss: 1.0000, cost time: 0.0568s
quick results: hits@[1, 5, 10, 50] = [22.191 38.764 46.348 68.539]%, time = 1.018 s
epoch 131, avg. triple loss: -0.0767, cost time: 2.1497s
epoch 131, sim loss: 1.0000, cost time: 0.0257s
epoch 132, avg. triple loss: -0.0766, cost time: 2.6045s
epoch 132, sim loss: 1.0000, cost time: 0.1202s
epoch 133, avg. triple loss: -0.0765, cost time: 2.5661s
epoch 133, sim loss: 1.0000, cost time: 0.0699s
epoch 134, avg. triple loss: -0.0766, cost time: 2.6049s
epoch 134, sim loss: 1.0000, cost time: 0.0495s
epoch 135, avg. triple loss: -0.0773, cost time: 2.3809s
epoch 135, sim loss: 1.0000, cost time: 0.0207s
epoch 136, avg. triple loss: -0.0772, cost time: 2.3124s
epoch 136, sim loss: 1.0000, cost time: 0.0457s
epoch 137, avg. triple loss: -0.0769, cost time: 2.6328s
epoch 137, sim loss: 1.0000, cost time: 0.1089s
epoch 138, avg. triple loss: -0.0769, cost time: 2.3242s
epoch 138, sim loss: 1.0000, cost time: 0.0401s
epoch 139, avg. triple loss: -0.0771, cost time: 2.4927s
epoch 139, sim loss: 1.0000, cost time: 0.0330s
epoch 140, avg. triple loss: -0.0771, cost time: 2.5247s
epoch 140, sim loss: 1.0000, cost time: 0.0505s
quick results: hits@[1, 5, 10, 50] = [21.348 35.112 43.258 64.888]%, time = 0.929 s
epoch 141, avg. triple loss: -0.0772, cost time: 2.6230s
epoch 141, sim loss: 1.0000, cost time: 0.0659s
epoch 142, avg. triple loss: -0.0776, cost time: 2.1862s
epoch 142, sim loss: 1.0000, cost time: 0.0214s
epoch 143, avg. triple loss: -0.0771, cost time: 2.3898s
epoch 143, sim loss: 1.0000, cost time: 0.0435s
epoch 144, avg. triple loss: -0.0772, cost time: 2.1513s
epoch 144, sim loss: 1.0000, cost time: 0.0338s
epoch 145, avg. triple loss: -0.0777, cost time: 2.7459s
epoch 145, sim loss: 1.0000, cost time: 0.0697s
epoch 146, avg. triple loss: -0.0775, cost time: 2.3701s
epoch 146, sim loss: 1.0000, cost time: 0.0510s
epoch 147, avg. triple loss: -0.0779, cost time: 2.5422s
epoch 147, sim loss: 1.0000, cost time: 0.0945s
epoch 148, avg. triple loss: -0.0775, cost time: 2.6953s
epoch 148, sim loss: 1.0000, cost time: 0.0431s
epoch 149, avg. triple loss: -0.0778, cost time: 2.6694s
epoch 149, sim loss: 1.0000, cost time: 0.0634s
epoch 150, avg. triple loss: -0.0776, cost time: 2.1474s
epoch 150, sim loss: 1.0000, cost time: 0.0313s
quick results: hits@[1, 5, 10, 50] = [20.506 33.708 42.697 71.91 ]%, time = 0.859 s
== should early stop ==
Training ends. Total time = 476.161 s.
accurate results: hits@[1, 5, 10, 50] = [21.464 37.65 46.376 71.288]%, mr = 58.687, mrr = 0.298368, time = 1.259 s
accurate results with csls: csls=10, hits@[1, 5, 10, 50] = [28.36 44.405 52.991 78.466]%, mr = 37.954, mrr = 0.368565, time = 1.467 s
Results saved!
../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/kg1_ent_ids saved.
../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/kg2_ent_ids saved.
../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/kg1_rel_ids saved.
../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/kg2_rel_ids saved.
../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/kg1_attr_ids saved.
../../output/results/Paper/eCommerceData/JAPE/LLM-LLM/721_5fold/1/20231020224346/kg2_attr_ids saved.
Embeddings saved!
Total run time = 540.868 s.