train_entity.py 头实体表示学习模型训练精度只有63

[Hanlard]

训练了很多epoch，开发集精度只有63 看了论文原文，并没有提到这部分的训练效果，请问作者也是这样吗？ 我感觉这个低了后续任务肯定受影响的 Dev Accuracy: 0.6357314148681055 411 17 40001 2049/2372 86% 0.003043 431 18 42001 1677/2372 71% 0.003203 451 19 44001 1305/2372 55% 0.002822 471 20 46001 933/2372 39% 0.003007 490 21 48001 561/2372 24% 0.003182 Dev Accuracy: 0.6398081534772182 513 22 50001 189/2372 8% 0.003154 533 22 52001 2189/2372 92% 0.002966 552 23 54001 1817/2372 77% 0.002975 572 24 56001 1445/2372 61% 0.002783 592 25 58001 1073/2372 45% 0.003067 Dev Accuracy: 0.6352517985611511 615 26 60001 701/2372 30% 0.002484 634 27 62001 329/2372 14% 0.002541 654 27 64001 2329/2372 98% 0.002770 674 28 66001 1957/2372 83% 0.002673 694 29 68001 1585/2372 67% 0.003463 Dev Accuracy: 0.6352517985611511 716 30 70001 1213/2372 51% 0.002752 736 31 72001 841/2372 35% 0.002837 756 32 74001 469/2372 20% 0.002801 776 33 76001 97/2372 4% 0.002722 795 33 78001 2097/2372 88% 0.002720 Dev Accuracy: 0.6302158273381295 818 34 80001 1725/2372 73% 0.002518 838 35 82001 1353/2372 57% 0.002832 858 36 84001 981/2372 41% 0.002269 878 37 86001 609/2372 26% 0.002469 898 38 88001 237/2372 10% 0.002821