关于半监督训练学习率问题

1、半监督从头训练学习率截取部分如下，从epoch54后面学习率都为0.01,burn_epochs=220：
epoch | train/box_loss | train/obj_loss | train/cls_loss | metrics/precision | metrics/recall | metrics/mAP_0.5 | metrics/mAP_0.5:0.95 | val/box_loss | val/obj_loss | val/cls_loss | x/lr0 | x/lr1 | x/lr2
50 0.045489 0.0052034 0 0 0 0 0 0 0 0 0.00917 0.00917 0.01747
51 0.044976 0.0052962 0 0 0 0 0 0 0 0 0.00935 0.00935 0.01585
52 0.043255 0.0051407 0 0 0 0 0 0 0 0 0.00953 0.00953 0.01423
53 0.044804 0.0053863 0 0 0 0 0 0 0 0 0.00971 0.00971 0.01261
54 0.044136 0.0049189 0 0 0 0 0 0 0 0 0.00989 0.00989 0.01099
55 0.042046 0.0052086 0 0 0 0 0 0 0 0 0.01 0.01 0.01
56 0.04328 0.004892 0 0 0 0 0 0 0 0 0.01 0.01 0.01
57 0.042468 0.0050412 0 0 0 0 0 0 0 0 0.01 0.01 0.01
58 0.043239 0.0051044 0 0 0 0 0 0 0 0 0.01 0.01 0.01
59 0.041122 0.0047628 0 0 0 0 0 0 0 0 0.01 0.01 0.01
60 0.041649 0.0048522 0 0 0 0 0 0 0 0 0.01 0.01 0.01
61 0.040692 0.0050476 0 0 0 0 0 0 0 0 0.01 0.01 0.01
62 0.038645 0.0047481 0 0 0 0 0 0 0 0 0.01 0.01 0.01

2、半监督训练加载labled10%训练好的模型epoch210接着训练,burn_epochs=220,后面的学习率都是0.01：
epoch | train/box_loss | train/obj_loss | train/cls_loss | metrics/precision | metrics/recall | metrics/mAP_0.5 | metrics/mAP_0.5:0.95 | val/box_loss | val/obj_loss | val/cls_loss | x/lr0 | x/lr1 | x/lr2
211 | 0.027092 | 0.002975 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01 | 0.01 | 0.01
212 | 0.025645 | 0.003046 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01 | 0.01 | 0.01
213 | 0.025966 | 0.003221 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01 | 0.01 | 0.01
214 | 0.025256 | 0.003216 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01 | 0.01 | 0.01
215 | 0.025347 | 0.003051 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01 | 0.01 | 0.01

我想请问下两个问题：
1、为什么yolov5l全监督训练配置文件中lrf设置为0.1，而半监督训练配置文件中lrf设置为1.0呢？这个有什么说法吗？
2、上述训练方式1的结果比方式2的结果差很多