The losses value from train_Caltech are higher than authors

[T109318049]

When I train the Caltech code from https://github.com/dominikandreas/CSP, the records show the loss value is very high.
I think that the value is the abnormal situation from cls_center, shown as below. But I have no idea to solve this issue.
The records from train_Caltech are shown as below:
"total loss" "cls" "regr_h" "offset"
0.146088 0.115322 0.009933 0.020833
0.098287 0.087741 0.002239 0.008307
0.071353 0.062760 0.001668 0.006925
0.081938 0.073539 0.001938 0.006461
0.073801 0.065529 0.001339 0.006932
0.072089 0.064259 0.001209 0.006621
0.067687 0.059619 0.001296 0.006772
0.064946 0.057368 0.001091 0.006488
0.061354 0.054006 0.001062 0.006286
0.061342 0.053803 0.001177 0.006362
0.061981 0.054710 0.001086 0.006185
0.058011 0.050864 0.001055 0.006091
0.055380 0.048392 0.001013 0.005975
0.059276 0.052155 0.001003 0.006118
0.051897 0.045055 0.000858 0.005984
0.052011 0.045238 0.000839 0.005935
0.055235 0.048431 0.000995 0.005809
0.053121 0.046175 0.000810 0.006136
0.054537 0.047586 0.001055 0.005896
0.050895 0.044234 0.000816 0.005845
0.051259 0.044498 0.000852 0.005909
0.050222 0.043484 0.000812 0.005926
0.049202 0.042674 0.000820 0.005707
0.047568 0.041040 0.000794 0.005733
0.045857 0.039506 0.000708 0.005643
0.049599 0.043301 0.000772 0.005527
0.046297 0.040108 0.000747 0.005442
0.045776 0.039386 0.000682 0.005708
0.047359 0.041113 0.000751 0.005495
0.044618 0.038325 0.000724 0.005569
0.044197 0.037804 0.000705 0.005688
0.043063 0.036738 0.000680 0.005645
0.044264 0.038139 0.000707 0.005418
0.041878 0.035751 0.000642 0.005485
0.044452 0.038305 0.000699 0.005448
0.042483 0.036077 0.000710 0.005695
0.044659 0.038537 0.000726 0.005396
0.041108 0.035030 0.000636 0.005442
0.040449 0.034342 0.000665 0.005442
0.040523 0.034651 0.000586 0.005286
0.040542 0.034645 0.000655 0.005242
0.039925 0.033994 0.000614 0.005317
0.040263 0.034208 0.000649 0.005406
0.039177 0.033443 0.000596 0.005138
0.037185 0.031399 0.000609 0.005177
0.041520 0.035570 0.000676 0.005274
0.039260 0.033446 0.000643 0.005171
0.038458 0.032674 0.000604 0.005180
0.038988 0.033193 0.000586 0.005209
0.038271 0.032380 0.000574 0.005317
0.037493 0.031569 0.000649 0.005276
0.038233 0.032616 0.000627 0.004990
0.037209 0.031312 0.000611 0.005286
0.038365 0.032619 0.000623 0.005123
0.036683 0.030863 0.000534 0.005286
0.036462 0.030927 0.000547 0.004988
0.035886 0.030214 0.000565 0.005108
0.037315 0.031443 0.000540 0.005332
0.035665 0.029956 0.000580 0.005128
0.036883 0.031298 0.000569 0.005016
0.036175 0.030355 0.000578 0.005241
0.034284 0.028385 0.000520 0.005379
0.034460 0.028736 0.000503 0.005221
0.034561 0.028825 0.000544 0.005192
0.035108 0.029526 0.000535 0.005047
0.033300 0.027814 0.000516 0.004970
0.035685 0.030010 0.000626 0.005049
0.034709 0.029089 0.000552 0.005067
0.032829 0.027182 0.000552 0.005095
0.034950 0.029222 0.000549 0.005179
0.035355 0.029635 0.000521 0.005199
0.033097 0.027575 0.000506 0.005016
0.034409 0.028776 0.000539 0.005094
0.034374 0.028723 0.000560 0.005091
0.033462 0.028019 0.000502 0.004941
0.031856 0.026466 0.000501 0.004889
0.034407 0.028888 0.000542 0.004977
0.033637 0.028005 0.000525 0.005106
0.032011 0.026455 0.000506 0.005049
0.032594 0.027016 0.000507 0.005072
0.031713 0.026079 0.000506 0.005128
0.032270 0.026873 0.000550 0.004847
0.033212 0.027798 0.000508 0.004907
0.033275 0.027806 0.000561 0.004908
0.031593 0.026026 0.000524 0.005043
0.033019 0.027241 0.000543 0.005235
0.031242 0.025833 0.000487 0.004922
0.033085 0.027534 0.000545 0.005007
0.032539 0.027065 0.000514 0.004960
0.031214 0.025757 0.000496 0.004960
0.031400 0.026045 0.000475 0.004880
0.030927 0.025401 0.000532 0.004995
0.031312 0.025998 0.000474 0.004839
0.031789 0.026305 0.000497 0.004988
0.031681 0.026299 0.000518 0.004863
0.029155 0.023938 0.000507 0.004711
0.028076 0.022962 0.000447 0.004667
0.030467 0.025188 0.000475 0.004803
0.031895 0.026434 0.000499 0.004961
0.030741 0.025282 0.000505 0.004954
0.030523 0.025147 0.000490 0.004887
0.031197 0.025962 0.000495 0.004740
0.028096 0.022867 0.000463 0.004767
0.029270 0.023728 0.000469 0.005072
0.030056 0.024727 0.000470 0.004859
0.029694 0.024355 0.000457 0.004883
0.029383 0.024017 0.000482 0.004884
0.029807 0.024387 0.000506 0.004914
0.030971 0.025645 0.000495 0.004831
0.031964 0.026566 0.000506 0.004892
0.030898 0.025541 0.000504 0.004853
0.029556 0.024205 0.000474 0.004878
0.028333 0.023096 0.000453 0.004784
0.028542 0.023254 0.000438 0.004850
0.028839 0.023586 0.000491 0.004762
0.029530 0.024289 0.000471 0.004770
0.030640 0.025408 0.000454 0.004779
0.030001 0.024737 0.000458 0.004806
0.029234 0.023925 0.000518 0.004791
0.028570 0.023454 0.000488 0.004627

Here is the version from the modules:
Python:3.6
Keras:2.0.8
Tensorflow: 1.14.0
py-OpenCV: 3.4.2

If anyone knows what the reason is, please answer me, thanks!