-
Notifications
You must be signed in to change notification settings - Fork 4
/
Copy pathHCT_ActivityNet.txt
11276 lines (11276 loc) · 827 KB
/
HCT_ActivityNet.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
Experiment directory: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet
Preparing the dataloaders ...
Loading dataset ActivityNet_val1_trainval in ram ...
Finish loading dataset ActivityNet_val1_trainval in ram, taking 747.427943944931 s.
Loading dataset ActivityNet_val1_test in ram ...
Finish loading dataset ActivityNet_val1_test in ram, taking 349.8234634399414 s.
Loading dataset ActivityNet_val1_test in ram ...
Finish loading dataset ActivityNet_val1_test in ram, taking 218.17129564285278 s.
Training ...
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch0.pth ...
Done in 1.520s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch0.pth ...
Done in 2.987s
epoch : 0
loss : 0
learning_rate : 5e-05
n_samples : 0
n_steps : 0
ActivityNet_val1_test/t2v_metrics/R1: 0.06101281269066504
ActivityNet_val1_test/t2v_metrics/R5: 0.14236322961155176
ActivityNet_val1_test/t2v_metrics/R10: 0.26438885499288184
ActivityNet_val1_test/t2v_metrics/R50: 0.7931665649786455
ActivityNet_val1_test/t2v_metrics/MedR: 2497.0
ActivityNet_val1_test/t2v_metrics/MeanR: 2496.692393736018
ActivityNet_val1_test/t2v_metrics/geometric_mean_R1-R5-R10: 0.1319331730062304
ActivityNet_val1_test/v2t_metrics/R1: 0.0
ActivityNet_val1_test/v2t_metrics/R5: 0.04067520846044336
ActivityNet_val1_test/v2t_metrics/R10: 0.08135041692088672
ActivityNet_val1_test/v2t_metrics/R50: 0.8135041692088671
ActivityNet_val1_test/v2t_metrics/MedR: 2562.0
ActivityNet_val1_test/v2t_metrics/MeanR: 2538.698901769372
ActivityNet_val1_test/v2t_metrics/geometric_mean_R1-R5-R10: 0.0
mnt_best : 0.1319331730062304
not_improved_count: 0
Train Epoch: 1 [1/1000 32/32000 (0%)] Loss: 7.00511 batch_time=23.65852
Train Epoch: 1 [6/1000 192/32000 (1%)] Loss: 6.73680 batch_time=0.23835
Train Epoch: 1 [11/1000 352/32000 (1%)] Loss: 6.43263 batch_time=0.27431
Train Epoch: 1 [16/1000 512/32000 (2%)] Loss: 5.76334 batch_time=0.22330
Train Epoch: 1 [21/1000 672/32000 (2%)] Loss: 5.59247 batch_time=0.19955
Train Epoch: 1 [26/1000 832/32000 (3%)] Loss: 4.62418 batch_time=0.19883
Train Epoch: 1 [31/1000 992/32000 (3%)] Loss: 4.85737 batch_time=0.20127
Train Epoch: 1 [36/1000 1152/32000 (4%)] Loss: 3.46187 batch_time=0.21861
Train Epoch: 1 [41/1000 1312/32000 (4%)] Loss: 3.21316 batch_time=0.19860
Train Epoch: 1 [46/1000 1472/32000 (5%)] Loss: 2.77478 batch_time=0.19564
Train Epoch: 1 [51/1000 1632/32000 (5%)] Loss: 3.24381 batch_time=0.19912
Train Epoch: 1 [56/1000 1792/32000 (6%)] Loss: 3.11314 batch_time=0.19874
Train Epoch: 1 [61/1000 1952/32000 (6%)] Loss: 2.86063 batch_time=0.21592
Train Epoch: 1 [66/1000 2112/32000 (7%)] Loss: 2.23190 batch_time=0.23328
Train Epoch: 1 [71/1000 2272/32000 (7%)] Loss: 1.93296 batch_time=0.19712
Train Epoch: 1 [76/1000 2432/32000 (8%)] Loss: 2.05100 batch_time=0.30929
Train Epoch: 1 [81/1000 2592/32000 (8%)] Loss: 2.46668 batch_time=0.19514
Train Epoch: 1 [86/1000 2752/32000 (9%)] Loss: 2.00671 batch_time=0.19792
Train Epoch: 1 [91/1000 2912/32000 (9%)] Loss: 1.82645 batch_time=0.19713
Train Epoch: 1 [96/1000 3072/32000 (10%)] Loss: 2.21227 batch_time=0.19910
Train Epoch: 1 [101/1000 3232/32000 (10%)] Loss: 1.58894 batch_time=0.19755
Train Epoch: 1 [106/1000 3392/32000 (11%)] Loss: 1.83536 batch_time=0.19806
Train Epoch: 1 [111/1000 3552/32000 (11%)] Loss: 1.75286 batch_time=0.19965
Train Epoch: 1 [116/1000 3712/32000 (12%)] Loss: 1.47594 batch_time=0.19499
Train Epoch: 1 [121/1000 3872/32000 (12%)] Loss: 1.29778 batch_time=0.20088
Train Epoch: 1 [126/1000 4032/32000 (13%)] Loss: 1.47550 batch_time=0.20127
Train Epoch: 1 [131/1000 4192/32000 (13%)] Loss: 1.44605 batch_time=0.21312
Train Epoch: 1 [136/1000 4352/32000 (14%)] Loss: 1.53063 batch_time=0.32355
Train Epoch: 1 [141/1000 4512/32000 (14%)] Loss: 1.67056 batch_time=0.20354
Train Epoch: 1 [146/1000 4672/32000 (15%)] Loss: 1.07022 batch_time=0.20120
Train Epoch: 1 [151/1000 4832/32000 (15%)] Loss: 1.18145 batch_time=0.42286
Train Epoch: 1 [156/1000 4992/32000 (16%)] Loss: 1.44604 batch_time=0.20457
Train Epoch: 1 [161/1000 5152/32000 (16%)] Loss: 1.15438 batch_time=0.19727
Train Epoch: 1 [166/1000 5312/32000 (17%)] Loss: 1.10875 batch_time=0.19916
Train Epoch: 1 [171/1000 5472/32000 (17%)] Loss: 1.74742 batch_time=0.19696
Train Epoch: 1 [176/1000 5632/32000 (18%)] Loss: 1.04224 batch_time=0.20022
Train Epoch: 1 [181/1000 5792/32000 (18%)] Loss: 1.22549 batch_time=0.19841
Train Epoch: 1 [186/1000 5952/32000 (19%)] Loss: 1.30262 batch_time=0.22907
Train Epoch: 1 [191/1000 6112/32000 (19%)] Loss: 1.01029 batch_time=0.21693
Train Epoch: 1 [196/1000 6272/32000 (20%)] Loss: 1.02606 batch_time=0.21765
Train Epoch: 1 [201/1000 6432/32000 (20%)] Loss: 1.06845 batch_time=0.20374
Train Epoch: 1 [206/1000 6592/32000 (21%)] Loss: 1.07610 batch_time=0.19791
Train Epoch: 1 [211/1000 6752/32000 (21%)] Loss: 1.31792 batch_time=0.19484
Train Epoch: 1 [216/1000 6912/32000 (22%)] Loss: 0.90281 batch_time=0.19784
Train Epoch: 1 [221/1000 7072/32000 (22%)] Loss: 0.86013 batch_time=0.73736
Train Epoch: 1 [226/1000 7232/32000 (23%)] Loss: 1.00797 batch_time=0.19825
Train Epoch: 1 [231/1000 7392/32000 (23%)] Loss: 1.01562 batch_time=0.19435
Train Epoch: 1 [236/1000 7552/32000 (24%)] Loss: 1.13198 batch_time=0.21071
Train Epoch: 1 [241/1000 7712/32000 (24%)] Loss: 0.68714 batch_time=0.19632
Train Epoch: 1 [246/1000 7872/32000 (25%)] Loss: 1.28228 batch_time=0.19868
Train Epoch: 1 [251/1000 8032/32000 (25%)] Loss: 1.37596 batch_time=0.19477
Train Epoch: 1 [256/1000 8192/32000 (26%)] Loss: 0.93735 batch_time=0.20591
Train Epoch: 1 [261/1000 8352/32000 (26%)] Loss: 1.04570 batch_time=0.22442
Train Epoch: 1 [266/1000 8512/32000 (27%)] Loss: 1.16572 batch_time=0.19398
Train Epoch: 1 [271/1000 8672/32000 (27%)] Loss: 0.76884 batch_time=0.19492
Train Epoch: 1 [276/1000 8832/32000 (28%)] Loss: 0.81494 batch_time=0.20061
Train Epoch: 1 [281/1000 8992/32000 (28%)] Loss: 1.21093 batch_time=0.20433
Train Epoch: 1 [286/1000 9152/32000 (29%)] Loss: 1.12049 batch_time=0.19957
Train Epoch: 1 [291/1000 9312/32000 (29%)] Loss: 0.89909 batch_time=0.21121
Train Epoch: 1 [296/1000 9472/32000 (30%)] Loss: 1.26441 batch_time=0.19965
Train Epoch: 1 [301/1000 9632/32000 (30%)] Loss: 1.02829 batch_time=0.20739
Train Epoch: 1 [306/1000 9792/32000 (31%)] Loss: 1.01145 batch_time=0.20487
Train Epoch: 1 [311/1000 9952/32000 (31%)] Loss: 0.77196 batch_time=0.19697
Train Epoch: 1 [316/1000 10112/32000 (32%)] Loss: 0.75323 batch_time=0.19748
Train Epoch: 1 [321/1000 10272/32000 (32%)] Loss: 1.16620 batch_time=0.19686
Train Epoch: 1 [326/1000 10432/32000 (33%)] Loss: 0.91258 batch_time=0.23271
Train Epoch: 1 [331/1000 10592/32000 (33%)] Loss: 0.75070 batch_time=0.25192
Train Epoch: 1 [336/1000 10752/32000 (34%)] Loss: 0.66081 batch_time=0.19741
Train Epoch: 1 [341/1000 10912/32000 (34%)] Loss: 0.59788 batch_time=0.20896
Train Epoch: 1 [346/1000 11072/32000 (35%)] Loss: 0.84212 batch_time=0.19848
Train Epoch: 1 [351/1000 11232/32000 (35%)] Loss: 0.45554 batch_time=0.19963
Train Epoch: 1 [356/1000 11392/32000 (36%)] Loss: 0.64275 batch_time=0.22871
Train Epoch: 1 [361/1000 11552/32000 (36%)] Loss: 0.98215 batch_time=0.22607
Train Epoch: 1 [366/1000 11712/32000 (37%)] Loss: 0.65625 batch_time=0.19846
Train Epoch: 1 [371/1000 11872/32000 (37%)] Loss: 1.21270 batch_time=0.19565
Train Epoch: 1 [376/1000 12032/32000 (38%)] Loss: 0.67549 batch_time=0.19597
Train Epoch: 1 [381/1000 12192/32000 (38%)] Loss: 0.74709 batch_time=0.20328
Train Epoch: 1 [386/1000 12352/32000 (39%)] Loss: 0.71318 batch_time=0.24570
Train Epoch: 1 [391/1000 12512/32000 (39%)] Loss: 0.51506 batch_time=0.19668
Train Epoch: 1 [396/1000 12672/32000 (40%)] Loss: 0.63333 batch_time=0.30034
Train Epoch: 1 [401/1000 12832/32000 (40%)] Loss: 0.72042 batch_time=0.20020
Train Epoch: 1 [406/1000 12992/32000 (41%)] Loss: 0.87604 batch_time=0.19700
Train Epoch: 1 [411/1000 13152/32000 (41%)] Loss: 0.66045 batch_time=0.19654
Train Epoch: 1 [416/1000 13312/32000 (42%)] Loss: 0.58538 batch_time=0.20491
Train Epoch: 1 [421/1000 13472/32000 (42%)] Loss: 0.62878 batch_time=0.21722
Train Epoch: 1 [426/1000 13632/32000 (43%)] Loss: 0.43235 batch_time=0.19622
Train Epoch: 1 [431/1000 13792/32000 (43%)] Loss: 0.82961 batch_time=0.19785
Train Epoch: 1 [436/1000 13952/32000 (44%)] Loss: 0.79786 batch_time=0.20232
Train Epoch: 1 [441/1000 14112/32000 (44%)] Loss: 0.55949 batch_time=0.19848
Train Epoch: 1 [446/1000 14272/32000 (45%)] Loss: 0.51806 batch_time=0.20146
Train Epoch: 1 [451/1000 14432/32000 (45%)] Loss: 1.07430 batch_time=0.21246
Train Epoch: 1 [456/1000 14592/32000 (46%)] Loss: 0.41982 batch_time=0.31356
Train Epoch: 1 [461/1000 14752/32000 (46%)] Loss: 0.50561 batch_time=0.19894
Train Epoch: 1 [466/1000 14912/32000 (47%)] Loss: 0.60028 batch_time=0.19592
Train Epoch: 1 [471/1000 15072/32000 (47%)] Loss: 0.47289 batch_time=0.42848
Train Epoch: 1 [476/1000 15232/32000 (48%)] Loss: 0.82819 batch_time=0.19663
Train Epoch: 1 [481/1000 15392/32000 (48%)] Loss: 0.80065 batch_time=0.19546
Train Epoch: 1 [486/1000 15552/32000 (49%)] Loss: 0.42759 batch_time=0.19631
Train Epoch: 1 [491/1000 15712/32000 (49%)] Loss: 0.51908 batch_time=0.21559
Train Epoch: 1 [496/1000 15872/32000 (50%)] Loss: 0.45108 batch_time=0.19857
Train Epoch: 1 [501/1000 16032/32000 (50%)] Loss: 0.58335 batch_time=0.20626
Train Epoch: 1 [506/1000 16192/32000 (51%)] Loss: 0.39817 batch_time=0.19540
Train Epoch: 1 [511/1000 16352/32000 (51%)] Loss: 0.48664 batch_time=0.21261
Train Epoch: 1 [516/1000 16512/32000 (52%)] Loss: 0.48972 batch_time=0.21394
Train Epoch: 1 [521/1000 16672/32000 (52%)] Loss: 0.64087 batch_time=0.22691
Train Epoch: 1 [526/1000 16832/32000 (53%)] Loss: 0.54046 batch_time=0.19795
Train Epoch: 1 [531/1000 16992/32000 (53%)] Loss: 0.41685 batch_time=0.19471
Train Epoch: 1 [536/1000 17152/32000 (54%)] Loss: 0.69355 batch_time=0.19383
Train Epoch: 1 [541/1000 17312/32000 (54%)] Loss: 0.65338 batch_time=0.71556
Train Epoch: 1 [546/1000 17472/32000 (55%)] Loss: 0.62653 batch_time=0.19698
Train Epoch: 1 [551/1000 17632/32000 (55%)] Loss: 0.32335 batch_time=0.23902
Train Epoch: 1 [556/1000 17792/32000 (56%)] Loss: 0.87772 batch_time=0.20396
Train Epoch: 1 [561/1000 17952/32000 (56%)] Loss: 0.75809 batch_time=0.19928
Train Epoch: 1 [566/1000 18112/32000 (57%)] Loss: 0.65490 batch_time=0.20023
Train Epoch: 1 [571/1000 18272/32000 (57%)] Loss: 0.52941 batch_time=0.19705
Train Epoch: 1 [576/1000 18432/32000 (58%)] Loss: 0.57355 batch_time=0.20326
Train Epoch: 1 [581/1000 18592/32000 (58%)] Loss: 0.56348 batch_time=0.20892
Train Epoch: 1 [586/1000 18752/32000 (59%)] Loss: 0.57154 batch_time=0.19567
Train Epoch: 1 [591/1000 18912/32000 (59%)] Loss: 0.27119 batch_time=0.19720
Train Epoch: 1 [596/1000 19072/32000 (60%)] Loss: 0.57654 batch_time=0.19551
Train Epoch: 1 [601/1000 19232/32000 (60%)] Loss: 0.59584 batch_time=0.19814
Train Epoch: 1 [606/1000 19392/32000 (61%)] Loss: 0.70130 batch_time=0.19417
Train Epoch: 1 [611/1000 19552/32000 (61%)] Loss: 0.27738 batch_time=0.20623
Train Epoch: 1 [616/1000 19712/32000 (62%)] Loss: 0.57767 batch_time=0.19698
Train Epoch: 1 [621/1000 19872/32000 (62%)] Loss: 0.36182 batch_time=0.19697
Train Epoch: 1 [626/1000 20032/32000 (63%)] Loss: 0.83215 batch_time=0.20712
Train Epoch: 1 [631/1000 20192/32000 (63%)] Loss: 1.00477 batch_time=0.19602
Train Epoch: 1 [636/1000 20352/32000 (64%)] Loss: 0.55630 batch_time=0.19631
Train Epoch: 1 [641/1000 20512/32000 (64%)] Loss: 0.35836 batch_time=0.19562
Train Epoch: 1 [646/1000 20672/32000 (65%)] Loss: 0.38953 batch_time=0.25189
Train Epoch: 1 [651/1000 20832/32000 (65%)] Loss: 0.33657 batch_time=0.25347
Train Epoch: 1 [656/1000 20992/32000 (66%)] Loss: 0.44441 batch_time=0.20131
Train Epoch: 1 [661/1000 21152/32000 (66%)] Loss: 0.63116 batch_time=0.20649
Train Epoch: 1 [666/1000 21312/32000 (67%)] Loss: 0.67133 batch_time=0.20246
Train Epoch: 1 [671/1000 21472/32000 (67%)] Loss: 0.45796 batch_time=0.21321
Train Epoch: 1 [676/1000 21632/32000 (68%)] Loss: 0.38122 batch_time=0.21678
Train Epoch: 1 [681/1000 21792/32000 (68%)] Loss: 0.33617 batch_time=0.19855
Train Epoch: 1 [686/1000 21952/32000 (69%)] Loss: 0.63597 batch_time=0.19689
Train Epoch: 1 [691/1000 22112/32000 (69%)] Loss: 0.35430 batch_time=0.19861
Train Epoch: 1 [696/1000 22272/32000 (70%)] Loss: 0.42993 batch_time=0.19628
Train Epoch: 1 [701/1000 22432/32000 (70%)] Loss: 0.25668 batch_time=0.20187
Train Epoch: 1 [706/1000 22592/32000 (71%)] Loss: 0.53339 batch_time=0.23172
Train Epoch: 1 [711/1000 22752/32000 (71%)] Loss: 0.59068 batch_time=0.19831
Train Epoch: 1 [716/1000 22912/32000 (72%)] Loss: 0.47659 batch_time=0.29894
Train Epoch: 1 [721/1000 23072/32000 (72%)] Loss: 0.39790 batch_time=0.19962
Train Epoch: 1 [726/1000 23232/32000 (73%)] Loss: 0.47863 batch_time=0.19967
Train Epoch: 1 [731/1000 23392/32000 (73%)] Loss: 0.54359 batch_time=0.22139
Train Epoch: 1 [736/1000 23552/32000 (74%)] Loss: 0.63523 batch_time=0.19842
Train Epoch: 1 [741/1000 23712/32000 (74%)] Loss: 0.29988 batch_time=0.19489
Train Epoch: 1 [746/1000 23872/32000 (75%)] Loss: 0.64358 batch_time=0.19830
Train Epoch: 1 [751/1000 24032/32000 (75%)] Loss: 0.54935 batch_time=0.19937
Train Epoch: 1 [756/1000 24192/32000 (76%)] Loss: 0.43239 batch_time=0.19493
Train Epoch: 1 [761/1000 24352/32000 (76%)] Loss: 0.41844 batch_time=0.19872
Train Epoch: 1 [766/1000 24512/32000 (77%)] Loss: 0.62660 batch_time=0.19403
Train Epoch: 1 [771/1000 24672/32000 (77%)] Loss: 0.46551 batch_time=0.19858
Train Epoch: 1 [776/1000 24832/32000 (78%)] Loss: 0.56053 batch_time=0.31745
Train Epoch: 1 [781/1000 24992/32000 (78%)] Loss: 0.43135 batch_time=0.19534
Train Epoch: 1 [786/1000 25152/32000 (79%)] Loss: 0.42131 batch_time=0.19706
Train Epoch: 1 [791/1000 25312/32000 (79%)] Loss: 0.52451 batch_time=0.41159
Train Epoch: 1 [796/1000 25472/32000 (80%)] Loss: 0.37709 batch_time=0.19391
Train Epoch: 1 [801/1000 25632/32000 (80%)] Loss: 0.27547 batch_time=0.19472
Train Epoch: 1 [806/1000 25792/32000 (81%)] Loss: 0.17402 batch_time=0.19468
Train Epoch: 1 [811/1000 25952/32000 (81%)] Loss: 0.48329 batch_time=0.19486
Train Epoch: 1 [816/1000 26112/32000 (82%)] Loss: 0.24772 batch_time=0.19553
Train Epoch: 1 [821/1000 26272/32000 (82%)] Loss: 0.31269 batch_time=0.19432
Train Epoch: 1 [826/1000 26432/32000 (83%)] Loss: 0.36696 batch_time=0.20165
Train Epoch: 1 [831/1000 26592/32000 (83%)] Loss: 0.73672 batch_time=0.21826
Train Epoch: 1 [836/1000 26752/32000 (84%)] Loss: 0.29836 batch_time=0.21896
Train Epoch: 1 [841/1000 26912/32000 (84%)] Loss: 0.59365 batch_time=0.19719
Train Epoch: 1 [846/1000 27072/32000 (85%)] Loss: 0.31775 batch_time=0.19693
Train Epoch: 1 [851/1000 27232/32000 (85%)] Loss: 0.54695 batch_time=0.19655
Train Epoch: 1 [856/1000 27392/32000 (86%)] Loss: 0.64151 batch_time=0.19748
Train Epoch: 1 [861/1000 27552/32000 (86%)] Loss: 0.41373 batch_time=0.72073
Train Epoch: 1 [866/1000 27712/32000 (87%)] Loss: 0.27003 batch_time=0.19592
Train Epoch: 1 [871/1000 27872/32000 (87%)] Loss: 0.31432 batch_time=0.19569
Train Epoch: 1 [876/1000 28032/32000 (88%)] Loss: 0.34229 batch_time=0.19931
Train Epoch: 1 [881/1000 28192/32000 (88%)] Loss: 0.47788 batch_time=0.20392
Train Epoch: 1 [886/1000 28352/32000 (89%)] Loss: 0.44340 batch_time=0.19823
Train Epoch: 1 [891/1000 28512/32000 (89%)] Loss: 0.29351 batch_time=0.19469
Train Epoch: 1 [896/1000 28672/32000 (90%)] Loss: 0.65366 batch_time=0.20214
Train Epoch: 1 [901/1000 28832/32000 (90%)] Loss: 0.61052 batch_time=0.22735
Train Epoch: 1 [906/1000 28992/32000 (91%)] Loss: 0.34902 batch_time=0.19296
Train Epoch: 1 [911/1000 29152/32000 (91%)] Loss: 0.38420 batch_time=0.20419
Train Epoch: 1 [916/1000 29312/32000 (92%)] Loss: 0.24746 batch_time=0.20217
Train Epoch: 1 [921/1000 29472/32000 (92%)] Loss: 0.61751 batch_time=0.19465
Train Epoch: 1 [926/1000 29632/32000 (93%)] Loss: 0.48651 batch_time=0.19923
Train Epoch: 1 [931/1000 29792/32000 (93%)] Loss: 0.28367 batch_time=0.20006
Train Epoch: 1 [936/1000 29952/32000 (94%)] Loss: 0.34580 batch_time=0.20082
Train Epoch: 1 [941/1000 30112/32000 (94%)] Loss: 0.40681 batch_time=0.22426
Train Epoch: 1 [946/1000 30272/32000 (95%)] Loss: 0.29918 batch_time=0.19710
Train Epoch: 1 [951/1000 30432/32000 (95%)] Loss: 0.26016 batch_time=0.19809
Train Epoch: 1 [956/1000 30592/32000 (96%)] Loss: 0.50376 batch_time=0.19726
Train Epoch: 1 [961/1000 30752/32000 (96%)] Loss: 0.44413 batch_time=0.26965
Train Epoch: 1 [966/1000 30912/32000 (97%)] Loss: 0.49936 batch_time=0.25165
Train Epoch: 1 [971/1000 31072/32000 (97%)] Loss: 0.36222 batch_time=0.26389
Train Epoch: 1 [976/1000 31232/32000 (98%)] Loss: 0.23375 batch_time=0.20070
Train Epoch: 1 [981/1000 31392/32000 (98%)] Loss: 0.27866 batch_time=0.22381
Train Epoch: 1 [986/1000 31552/32000 (99%)] Loss: 0.26538 batch_time=0.19762
Train Epoch: 1 [991/1000 31712/32000 (99%)] Loss: 0.27731 batch_time=0.20133
Train Epoch: 1 [996/1000 31872/32000 (100%)] Loss: 0.16317 batch_time=0.21742
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch1.pth ...
Done in 3.729s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch1.pth ...
Done in 7.409s
epoch : 1
loss : 0.9536369983702898
learning_rate : 5e-05
n_samples : 32000
n_steps : 1000
ActivityNet_val1_test/t2v_metrics/R1: 14.602399837299167
ActivityNet_val1_test/t2v_metrics/R5: 41.63107585926378
ActivityNet_val1_test/t2v_metrics/R10: 58.08419768151312
ActivityNet_val1_test/t2v_metrics/R50: 89.79052267642872
ActivityNet_val1_test/t2v_metrics/MedR: 8.0
ActivityNet_val1_test/t2v_metrics/MeanR: 26.958918039454954
ActivityNet_val1_test/t2v_metrics/geometric_mean_R1-R5-R10: 32.8070077876577
ActivityNet_val1_test/v2t_metrics/R1: 15.761643278421802
ActivityNet_val1_test/v2t_metrics/R5: 42.38356721578198
ActivityNet_val1_test/v2t_metrics/R10: 58.95871466341265
ActivityNet_val1_test/v2t_metrics/R50: 90.40065080333537
ActivityNet_val1_test/v2t_metrics/MedR: 8.0
ActivityNet_val1_test/v2t_metrics/MeanR: 25.95688427903193
ActivityNet_val1_test/v2t_metrics/geometric_mean_R1-R5-R10: 34.023762320765165
mnt_best : 32.8070077876577
not_improved_count: 0
Train Epoch: 2 [1/1000 32/32000 (0%)] Loss: 0.35011 batch_time=21.69812
Train Epoch: 2 [6/1000 192/32000 (1%)] Loss: 0.47172 batch_time=0.19541
Train Epoch: 2 [11/1000 352/32000 (1%)] Loss: 0.41536 batch_time=0.20990
Train Epoch: 2 [16/1000 512/32000 (2%)] Loss: 0.41122 batch_time=0.23217
Train Epoch: 2 [21/1000 672/32000 (2%)] Loss: 0.38269 batch_time=0.21724
Train Epoch: 2 [26/1000 832/32000 (3%)] Loss: 0.58898 batch_time=0.22149
Train Epoch: 2 [31/1000 992/32000 (3%)] Loss: 0.18987 batch_time=0.22110
Train Epoch: 2 [36/1000 1152/32000 (4%)] Loss: 0.20931 batch_time=0.20029
Train Epoch: 2 [41/1000 1312/32000 (4%)] Loss: 0.45014 batch_time=0.21624
Train Epoch: 2 [46/1000 1472/32000 (5%)] Loss: 0.45393 batch_time=0.20023
Train Epoch: 2 [51/1000 1632/32000 (5%)] Loss: 0.44511 batch_time=0.19795
Train Epoch: 2 [56/1000 1792/32000 (6%)] Loss: 0.40143 batch_time=0.19830
Train Epoch: 2 [61/1000 1952/32000 (6%)] Loss: 0.28552 batch_time=0.19769
Train Epoch: 2 [66/1000 2112/32000 (7%)] Loss: 0.27092 batch_time=0.19421
Train Epoch: 2 [71/1000 2272/32000 (7%)] Loss: 0.48762 batch_time=0.20599
Train Epoch: 2 [76/1000 2432/32000 (8%)] Loss: 0.24278 batch_time=0.20435
Train Epoch: 2 [81/1000 2592/32000 (8%)] Loss: 0.22912 batch_time=0.28437
Train Epoch: 2 [86/1000 2752/32000 (9%)] Loss: 0.09894 batch_time=0.31450
Train Epoch: 2 [91/1000 2912/32000 (9%)] Loss: 0.37099 batch_time=0.20691
Train Epoch: 2 [96/1000 3072/32000 (10%)] Loss: 0.51438 batch_time=0.20905
Train Epoch: 2 [101/1000 3232/32000 (10%)] Loss: 0.30767 batch_time=0.20852
Train Epoch: 2 [106/1000 3392/32000 (11%)] Loss: 0.33475 batch_time=0.20258
Train Epoch: 2 [111/1000 3552/32000 (11%)] Loss: 0.25119 batch_time=0.26839
Train Epoch: 2 [116/1000 3712/32000 (12%)] Loss: 0.39050 batch_time=0.19764
Train Epoch: 2 [121/1000 3872/32000 (12%)] Loss: 0.17813 batch_time=0.21691
Train Epoch: 2 [126/1000 4032/32000 (13%)] Loss: 0.25755 batch_time=0.19548
Train Epoch: 2 [131/1000 4192/32000 (13%)] Loss: 0.44349 batch_time=0.20580
Train Epoch: 2 [136/1000 4352/32000 (14%)] Loss: 0.38055 batch_time=0.22681
Train Epoch: 2 [141/1000 4512/32000 (14%)] Loss: 0.53568 batch_time=0.23005
Train Epoch: 2 [146/1000 4672/32000 (15%)] Loss: 0.40667 batch_time=0.21189
Train Epoch: 2 [151/1000 4832/32000 (15%)] Loss: 0.25957 batch_time=0.20304
Train Epoch: 2 [156/1000 4992/32000 (16%)] Loss: 0.36148 batch_time=0.20795
Train Epoch: 2 [161/1000 5152/32000 (16%)] Loss: 0.45862 batch_time=0.19894
Train Epoch: 2 [166/1000 5312/32000 (17%)] Loss: 0.16498 batch_time=0.19989
Train Epoch: 2 [171/1000 5472/32000 (17%)] Loss: 0.28137 batch_time=0.19577
Train Epoch: 2 [176/1000 5632/32000 (18%)] Loss: 0.34704 batch_time=0.20451
Train Epoch: 2 [181/1000 5792/32000 (18%)] Loss: 0.32475 batch_time=0.20170
Train Epoch: 2 [186/1000 5952/32000 (19%)] Loss: 0.20646 batch_time=0.20274
Train Epoch: 2 [191/1000 6112/32000 (19%)] Loss: 0.26462 batch_time=0.19681
Train Epoch: 2 [196/1000 6272/32000 (20%)] Loss: 0.31318 batch_time=0.19717
Train Epoch: 2 [201/1000 6432/32000 (20%)] Loss: 0.29329 batch_time=0.21383
Train Epoch: 2 [206/1000 6592/32000 (21%)] Loss: 0.33909 batch_time=0.19605
Train Epoch: 2 [211/1000 6752/32000 (21%)] Loss: 0.32040 batch_time=0.90454
Train Epoch: 2 [216/1000 6912/32000 (22%)] Loss: 0.21414 batch_time=0.21524
Train Epoch: 2 [221/1000 7072/32000 (22%)] Loss: 0.27418 batch_time=0.19606
Train Epoch: 2 [226/1000 7232/32000 (23%)] Loss: 0.24939 batch_time=0.19719
Train Epoch: 2 [231/1000 7392/32000 (23%)] Loss: 0.39577 batch_time=0.19640
Train Epoch: 2 [236/1000 7552/32000 (24%)] Loss: 0.15634 batch_time=0.19848
Train Epoch: 2 [241/1000 7712/32000 (24%)] Loss: 0.42535 batch_time=0.22288
Train Epoch: 2 [246/1000 7872/32000 (25%)] Loss: 0.28831 batch_time=0.19833
Train Epoch: 2 [251/1000 8032/32000 (25%)] Loss: 0.29510 batch_time=0.20663
Train Epoch: 2 [256/1000 8192/32000 (26%)] Loss: 0.39268 batch_time=0.19649
Train Epoch: 2 [261/1000 8352/32000 (26%)] Loss: 0.37089 batch_time=0.19735
Train Epoch: 2 [266/1000 8512/32000 (27%)] Loss: 0.42912 batch_time=0.19905
Train Epoch: 2 [271/1000 8672/32000 (27%)] Loss: 0.13985 batch_time=0.21244
Train Epoch: 2 [276/1000 8832/32000 (28%)] Loss: 0.41547 batch_time=0.43481
Train Epoch: 2 [281/1000 8992/32000 (28%)] Loss: 0.21759 batch_time=0.21364
Train Epoch: 2 [286/1000 9152/32000 (29%)] Loss: 0.24061 batch_time=0.20008
Train Epoch: 2 [291/1000 9312/32000 (29%)] Loss: 0.16605 batch_time=0.23124
Train Epoch: 2 [296/1000 9472/32000 (30%)] Loss: 0.24583 batch_time=0.19719
Train Epoch: 2 [301/1000 9632/32000 (30%)] Loss: 0.35865 batch_time=0.20458
Train Epoch: 2 [306/1000 9792/32000 (31%)] Loss: 0.17486 batch_time=0.22053
Train Epoch: 2 [311/1000 9952/32000 (31%)] Loss: 0.27696 batch_time=0.21841
Train Epoch: 2 [316/1000 10112/32000 (32%)] Loss: 0.29658 batch_time=0.20630
Train Epoch: 2 [321/1000 10272/32000 (32%)] Loss: 0.20841 batch_time=0.27682
Train Epoch: 2 [326/1000 10432/32000 (33%)] Loss: 0.46862 batch_time=0.19908
Train Epoch: 2 [331/1000 10592/32000 (33%)] Loss: 0.29797 batch_time=0.19566
Train Epoch: 2 [336/1000 10752/32000 (34%)] Loss: 0.24610 batch_time=0.23125
Train Epoch: 2 [341/1000 10912/32000 (34%)] Loss: 0.16340 batch_time=0.20777
Train Epoch: 2 [346/1000 11072/32000 (35%)] Loss: 0.17883 batch_time=0.21060
Train Epoch: 2 [351/1000 11232/32000 (35%)] Loss: 0.20451 batch_time=0.19665
Train Epoch: 2 [356/1000 11392/32000 (36%)] Loss: 0.21789 batch_time=0.20274
Train Epoch: 2 [361/1000 11552/32000 (36%)] Loss: 0.42451 batch_time=0.21427
Train Epoch: 2 [366/1000 11712/32000 (37%)] Loss: 0.34645 batch_time=0.19684
Train Epoch: 2 [371/1000 11872/32000 (37%)] Loss: 0.15171 batch_time=0.19622
Train Epoch: 2 [376/1000 12032/32000 (38%)] Loss: 0.24885 batch_time=0.21301
Train Epoch: 2 [381/1000 12192/32000 (38%)] Loss: 0.16461 batch_time=0.19904
Train Epoch: 2 [386/1000 12352/32000 (39%)] Loss: 0.33766 batch_time=0.19473
Train Epoch: 2 [391/1000 12512/32000 (39%)] Loss: 0.23066 batch_time=0.19960
Train Epoch: 2 [396/1000 12672/32000 (40%)] Loss: 0.28622 batch_time=0.19707
Train Epoch: 2 [401/1000 12832/32000 (40%)] Loss: 0.30700 batch_time=0.27751
Train Epoch: 2 [406/1000 12992/32000 (41%)] Loss: 0.29398 batch_time=0.34008
Train Epoch: 2 [411/1000 13152/32000 (41%)] Loss: 0.20655 batch_time=0.22814
Train Epoch: 2 [416/1000 13312/32000 (42%)] Loss: 0.26849 batch_time=0.19891
Train Epoch: 2 [421/1000 13472/32000 (42%)] Loss: 0.30017 batch_time=0.20815
Train Epoch: 2 [426/1000 13632/32000 (43%)] Loss: 0.29809 batch_time=0.19945
Train Epoch: 2 [431/1000 13792/32000 (43%)] Loss: 0.51597 batch_time=0.25260
Train Epoch: 2 [436/1000 13952/32000 (44%)] Loss: 0.28804 batch_time=0.23309
Train Epoch: 2 [441/1000 14112/32000 (44%)] Loss: 0.19631 batch_time=0.21506
Train Epoch: 2 [446/1000 14272/32000 (45%)] Loss: 0.42286 batch_time=0.19824
Train Epoch: 2 [451/1000 14432/32000 (45%)] Loss: 0.17645 batch_time=0.19918
Train Epoch: 2 [456/1000 14592/32000 (46%)] Loss: 0.35342 batch_time=0.22315
Train Epoch: 2 [461/1000 14752/32000 (46%)] Loss: 0.19142 batch_time=0.23800
Train Epoch: 2 [466/1000 14912/32000 (47%)] Loss: 0.26364 batch_time=0.19401
Train Epoch: 2 [471/1000 15072/32000 (47%)] Loss: 0.18214 batch_time=0.20672
Train Epoch: 2 [476/1000 15232/32000 (48%)] Loss: 0.17640 batch_time=0.20553
Train Epoch: 2 [481/1000 15392/32000 (48%)] Loss: 0.53099 batch_time=0.19592
Train Epoch: 2 [486/1000 15552/32000 (49%)] Loss: 0.26291 batch_time=0.20571
Train Epoch: 2 [491/1000 15712/32000 (49%)] Loss: 0.17078 batch_time=0.20305
Train Epoch: 2 [496/1000 15872/32000 (50%)] Loss: 0.16059 batch_time=0.21811
Train Epoch: 2 [501/1000 16032/32000 (50%)] Loss: 0.20887 batch_time=0.20440
Train Epoch: 2 [506/1000 16192/32000 (51%)] Loss: 0.19391 batch_time=0.19918
Train Epoch: 2 [511/1000 16352/32000 (51%)] Loss: 0.17497 batch_time=0.21192
Train Epoch: 2 [516/1000 16512/32000 (52%)] Loss: 0.33626 batch_time=0.19600
Train Epoch: 2 [521/1000 16672/32000 (52%)] Loss: 0.05868 batch_time=0.21415
Train Epoch: 2 [526/1000 16832/32000 (53%)] Loss: 0.32975 batch_time=0.19593
Train Epoch: 2 [531/1000 16992/32000 (53%)] Loss: 0.21498 batch_time=0.80514
Train Epoch: 2 [536/1000 17152/32000 (54%)] Loss: 0.45634 batch_time=0.19537
Train Epoch: 2 [541/1000 17312/32000 (54%)] Loss: 0.11366 batch_time=0.19549
Train Epoch: 2 [546/1000 17472/32000 (55%)] Loss: 0.23350 batch_time=0.20079
Train Epoch: 2 [551/1000 17632/32000 (55%)] Loss: 0.23337 batch_time=0.20242
Train Epoch: 2 [556/1000 17792/32000 (56%)] Loss: 0.36166 batch_time=0.19859
Train Epoch: 2 [561/1000 17952/32000 (56%)] Loss: 0.33313 batch_time=0.22362
Train Epoch: 2 [566/1000 18112/32000 (57%)] Loss: 0.25585 batch_time=0.19887
Train Epoch: 2 [571/1000 18272/32000 (57%)] Loss: 0.37668 batch_time=0.22832
Train Epoch: 2 [576/1000 18432/32000 (58%)] Loss: 0.36176 batch_time=0.19712
Train Epoch: 2 [581/1000 18592/32000 (58%)] Loss: 0.36277 batch_time=0.19900
Train Epoch: 2 [586/1000 18752/32000 (59%)] Loss: 0.34253 batch_time=0.20783
Train Epoch: 2 [591/1000 18912/32000 (59%)] Loss: 0.20030 batch_time=0.22738
Train Epoch: 2 [596/1000 19072/32000 (60%)] Loss: 0.33678 batch_time=0.48285
Train Epoch: 2 [601/1000 19232/32000 (60%)] Loss: 0.41497 batch_time=0.22011
Train Epoch: 2 [606/1000 19392/32000 (61%)] Loss: 0.25909 batch_time=0.21355
Train Epoch: 2 [611/1000 19552/32000 (61%)] Loss: 0.34866 batch_time=0.20332
Train Epoch: 2 [616/1000 19712/32000 (62%)] Loss: 0.63976 batch_time=0.21108
Train Epoch: 2 [621/1000 19872/32000 (62%)] Loss: 0.32985 batch_time=0.19842
Train Epoch: 2 [626/1000 20032/32000 (63%)] Loss: 0.34959 batch_time=0.20413
Train Epoch: 2 [631/1000 20192/32000 (63%)] Loss: 0.14438 batch_time=0.20769
Train Epoch: 2 [636/1000 20352/32000 (64%)] Loss: 0.31310 batch_time=0.20038
Train Epoch: 2 [641/1000 20512/32000 (64%)] Loss: 0.24206 batch_time=0.30075
Train Epoch: 2 [646/1000 20672/32000 (65%)] Loss: 0.38500 batch_time=0.19854
Train Epoch: 2 [651/1000 20832/32000 (65%)] Loss: 0.28480 batch_time=0.21302
Train Epoch: 2 [656/1000 20992/32000 (66%)] Loss: 0.26602 batch_time=0.23340
Train Epoch: 2 [661/1000 21152/32000 (66%)] Loss: 0.14123 batch_time=0.20768
Train Epoch: 2 [666/1000 21312/32000 (67%)] Loss: 0.20951 batch_time=0.21441
Train Epoch: 2 [671/1000 21472/32000 (67%)] Loss: 0.29247 batch_time=0.20949
Train Epoch: 2 [676/1000 21632/32000 (68%)] Loss: 0.34803 batch_time=0.20603
Train Epoch: 2 [681/1000 21792/32000 (68%)] Loss: 0.16330 batch_time=0.21590
Train Epoch: 2 [686/1000 21952/32000 (69%)] Loss: 0.40868 batch_time=0.19993
Train Epoch: 2 [691/1000 22112/32000 (69%)] Loss: 0.30274 batch_time=0.19685
Train Epoch: 2 [696/1000 22272/32000 (70%)] Loss: 0.10681 batch_time=0.20767
Train Epoch: 2 [701/1000 22432/32000 (70%)] Loss: 0.15713 batch_time=0.22866
Train Epoch: 2 [706/1000 22592/32000 (71%)] Loss: 0.19521 batch_time=0.20535
Train Epoch: 2 [711/1000 22752/32000 (71%)] Loss: 0.27271 batch_time=0.19854
Train Epoch: 2 [716/1000 22912/32000 (72%)] Loss: 0.31399 batch_time=0.22915
Train Epoch: 2 [721/1000 23072/32000 (72%)] Loss: 0.30638 batch_time=0.32183
Train Epoch: 2 [726/1000 23232/32000 (73%)] Loss: 0.36909 batch_time=0.33784
Train Epoch: 2 [731/1000 23392/32000 (73%)] Loss: 0.28322 batch_time=0.20869
Train Epoch: 2 [736/1000 23552/32000 (74%)] Loss: 0.24024 batch_time=0.19854
Train Epoch: 2 [741/1000 23712/32000 (74%)] Loss: 0.46304 batch_time=0.20755
Train Epoch: 2 [746/1000 23872/32000 (75%)] Loss: 0.35089 batch_time=0.21089
Train Epoch: 2 [751/1000 24032/32000 (75%)] Loss: 0.23718 batch_time=0.25764
Train Epoch: 2 [756/1000 24192/32000 (76%)] Loss: 0.23167 batch_time=0.19594
Train Epoch: 2 [761/1000 24352/32000 (76%)] Loss: 0.29053 batch_time=0.19531
Train Epoch: 2 [766/1000 24512/32000 (77%)] Loss: 0.25777 batch_time=0.19974
Train Epoch: 2 [771/1000 24672/32000 (77%)] Loss: 0.26872 batch_time=0.19544
Train Epoch: 2 [776/1000 24832/32000 (78%)] Loss: 0.15215 batch_time=0.21258
Train Epoch: 2 [781/1000 24992/32000 (78%)] Loss: 0.21515 batch_time=0.22356
Train Epoch: 2 [786/1000 25152/32000 (79%)] Loss: 0.15784 batch_time=0.22610
Train Epoch: 2 [791/1000 25312/32000 (79%)] Loss: 0.23943 batch_time=0.20031
Train Epoch: 2 [796/1000 25472/32000 (80%)] Loss: 0.33480 batch_time=0.19734
Train Epoch: 2 [801/1000 25632/32000 (80%)] Loss: 0.26890 batch_time=0.21971
Train Epoch: 2 [806/1000 25792/32000 (81%)] Loss: 0.14658 batch_time=0.21412
Train Epoch: 2 [811/1000 25952/32000 (81%)] Loss: 0.32743 batch_time=0.20521
Train Epoch: 2 [816/1000 26112/32000 (82%)] Loss: 0.24905 batch_time=0.21762
Train Epoch: 2 [821/1000 26272/32000 (82%)] Loss: 0.22774 batch_time=0.20492
Train Epoch: 2 [826/1000 26432/32000 (83%)] Loss: 0.23618 batch_time=0.20597
Train Epoch: 2 [831/1000 26592/32000 (83%)] Loss: 0.35621 batch_time=0.20725
Train Epoch: 2 [836/1000 26752/32000 (84%)] Loss: 0.32728 batch_time=0.20633
Train Epoch: 2 [841/1000 26912/32000 (84%)] Loss: 0.08457 batch_time=0.22826
Train Epoch: 2 [846/1000 27072/32000 (85%)] Loss: 0.13934 batch_time=0.20308
Train Epoch: 2 [851/1000 27232/32000 (85%)] Loss: 0.19753 batch_time=0.76844
Train Epoch: 2 [856/1000 27392/32000 (86%)] Loss: 0.27911 batch_time=0.20430
Train Epoch: 2 [861/1000 27552/32000 (86%)] Loss: 0.16337 batch_time=0.20092
Train Epoch: 2 [866/1000 27712/32000 (87%)] Loss: 0.45568 batch_time=0.20023
Train Epoch: 2 [871/1000 27872/32000 (87%)] Loss: 0.22488 batch_time=0.23519
Train Epoch: 2 [876/1000 28032/32000 (88%)] Loss: 0.14483 batch_time=0.19943
Train Epoch: 2 [881/1000 28192/32000 (88%)] Loss: 0.25152 batch_time=0.21612
Train Epoch: 2 [886/1000 28352/32000 (89%)] Loss: 0.24391 batch_time=0.21640
Train Epoch: 2 [891/1000 28512/32000 (89%)] Loss: 0.23908 batch_time=0.21078
Train Epoch: 2 [896/1000 28672/32000 (90%)] Loss: 0.27404 batch_time=0.19887
Train Epoch: 2 [901/1000 28832/32000 (90%)] Loss: 0.29191 batch_time=0.21414
Train Epoch: 2 [906/1000 28992/32000 (91%)] Loss: 0.20488 batch_time=0.19979
Train Epoch: 2 [911/1000 29152/32000 (91%)] Loss: 0.10986 batch_time=0.22530
Train Epoch: 2 [916/1000 29312/32000 (92%)] Loss: 0.19583 batch_time=0.47916
Train Epoch: 2 [921/1000 29472/32000 (92%)] Loss: 0.14350 batch_time=0.22241
Train Epoch: 2 [926/1000 29632/32000 (93%)] Loss: 0.22059 batch_time=0.19761
Train Epoch: 2 [931/1000 29792/32000 (93%)] Loss: 0.23229 batch_time=0.22229
Train Epoch: 2 [936/1000 29952/32000 (94%)] Loss: 0.06479 batch_time=0.20168
Train Epoch: 2 [941/1000 30112/32000 (94%)] Loss: 0.06658 batch_time=0.21191
Train Epoch: 2 [946/1000 30272/32000 (95%)] Loss: 0.32803 batch_time=0.21993
Train Epoch: 2 [951/1000 30432/32000 (95%)] Loss: 0.33906 batch_time=0.20178
Train Epoch: 2 [956/1000 30592/32000 (96%)] Loss: 0.22567 batch_time=0.20147
Train Epoch: 2 [961/1000 30752/32000 (96%)] Loss: 0.17612 batch_time=0.29628
Train Epoch: 2 [966/1000 30912/32000 (97%)] Loss: 0.19227 batch_time=0.21317
Train Epoch: 2 [971/1000 31072/32000 (97%)] Loss: 0.24253 batch_time=0.20350
Train Epoch: 2 [976/1000 31232/32000 (98%)] Loss: 0.34779 batch_time=0.23456
Train Epoch: 2 [981/1000 31392/32000 (98%)] Loss: 0.16449 batch_time=0.20587
Train Epoch: 2 [986/1000 31552/32000 (99%)] Loss: 0.15268 batch_time=0.23241
Train Epoch: 2 [991/1000 31712/32000 (99%)] Loss: 0.32576 batch_time=0.21113
Train Epoch: 2 [996/1000 31872/32000 (100%)] Loss: 0.26697 batch_time=0.22268
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch2.pth ...
Done in 4.178s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch2.pth ...
Done in 8.384s
removing stale ckpt [epoch 1] [took 0.05s]
removing stale ckpt [epoch 0] [took 0.02s]
epoch : 2
loss : 0.28030740085616707
learning_rate : 5e-05
n_samples : 64000
n_steps : 2000
ActivityNet_val1_test/t2v_metrics/R1: 16.127720154565793
ActivityNet_val1_test/t2v_metrics/R5: 44.132601179581044
ActivityNet_val1_test/t2v_metrics/R10: 61.70429123449258
ActivityNet_val1_test/t2v_metrics/R50: 91.98698393329266
ActivityNet_val1_test/t2v_metrics/MedR: 7.0
ActivityNet_val1_test/t2v_metrics/MeanR: 26.224323774659346
ActivityNet_val1_test/t2v_metrics/geometric_mean_R1-R5-R10: 35.28168278312381
ActivityNet_val1_test/v2t_metrics/R1: 17.368314012609314
ActivityNet_val1_test/v2t_metrics/R5: 47.142566605653855
ActivityNet_val1_test/v2t_metrics/R10: 63.57535082367297
ActivityNet_val1_test/v2t_metrics/R50: 92.73947528981085
ActivityNet_val1_test/v2t_metrics/MedR: 6.0
ActivityNet_val1_test/v2t_metrics/MeanR: 23.726865975188122
ActivityNet_val1_test/v2t_metrics/geometric_mean_R1-R5-R10: 37.33818619203601
mnt_best : 35.28168278312381
not_improved_count: 0
Train Epoch: 3 [1/1000 32/32000 (0%)] Loss: 0.40145 batch_time=21.38094
Train Epoch: 3 [6/1000 192/32000 (1%)] Loss: 0.14220 batch_time=0.31727
Train Epoch: 3 [11/1000 352/32000 (1%)] Loss: 0.19371 batch_time=0.20327
Train Epoch: 3 [16/1000 512/32000 (2%)] Loss: 0.15595 batch_time=0.27073
Train Epoch: 3 [21/1000 672/32000 (2%)] Loss: 0.19997 batch_time=0.29850
Train Epoch: 3 [26/1000 832/32000 (3%)] Loss: 0.21961 batch_time=0.20862
Train Epoch: 3 [31/1000 992/32000 (3%)] Loss: 0.28333 batch_time=0.20644
Train Epoch: 3 [36/1000 1152/32000 (4%)] Loss: 0.14482 batch_time=0.21156
Train Epoch: 3 [41/1000 1312/32000 (4%)] Loss: 0.36378 batch_time=0.19556
Train Epoch: 3 [46/1000 1472/32000 (5%)] Loss: 0.18860 batch_time=0.20888
Train Epoch: 3 [51/1000 1632/32000 (5%)] Loss: 0.15620 batch_time=0.23765
Train Epoch: 3 [56/1000 1792/32000 (6%)] Loss: 0.27208 batch_time=0.20703
Train Epoch: 3 [61/1000 1952/32000 (6%)] Loss: 0.24287 batch_time=0.23927
Train Epoch: 3 [66/1000 2112/32000 (7%)] Loss: 0.09561 batch_time=0.24310
Train Epoch: 3 [71/1000 2272/32000 (7%)] Loss: 0.33929 batch_time=0.20257
Train Epoch: 3 [76/1000 2432/32000 (8%)] Loss: 0.12244 batch_time=0.19620
Train Epoch: 3 [81/1000 2592/32000 (8%)] Loss: 0.28956 batch_time=0.28562
Train Epoch: 3 [86/1000 2752/32000 (9%)] Loss: 0.07750 batch_time=0.19695
Train Epoch: 3 [91/1000 2912/32000 (9%)] Loss: 0.12615 batch_time=0.70031
Train Epoch: 3 [96/1000 3072/32000 (10%)] Loss: 0.19556 batch_time=0.24641
Train Epoch: 3 [101/1000 3232/32000 (10%)] Loss: 0.18507 batch_time=0.21415
Train Epoch: 3 [106/1000 3392/32000 (11%)] Loss: 0.14148 batch_time=0.23889
Train Epoch: 3 [111/1000 3552/32000 (11%)] Loss: 0.12237 batch_time=0.22229
Train Epoch: 3 [116/1000 3712/32000 (12%)] Loss: 0.16505 batch_time=0.22767
Train Epoch: 3 [121/1000 3872/32000 (12%)] Loss: 0.04589 batch_time=0.22149
Train Epoch: 3 [126/1000 4032/32000 (13%)] Loss: 0.05972 batch_time=0.19855
Train Epoch: 3 [131/1000 4192/32000 (13%)] Loss: 0.19257 batch_time=0.19667
Train Epoch: 3 [136/1000 4352/32000 (14%)] Loss: 0.29628 batch_time=0.19606
Train Epoch: 3 [141/1000 4512/32000 (14%)] Loss: 0.11072 batch_time=0.20772
Train Epoch: 3 [146/1000 4672/32000 (15%)] Loss: 0.14101 batch_time=0.20012
Train Epoch: 3 [151/1000 4832/32000 (15%)] Loss: 0.21167 batch_time=0.20028
Train Epoch: 3 [156/1000 4992/32000 (16%)] Loss: 0.23070 batch_time=0.20821
Train Epoch: 3 [161/1000 5152/32000 (16%)] Loss: 0.21004 batch_time=0.21090
Train Epoch: 3 [166/1000 5312/32000 (17%)] Loss: 0.21611 batch_time=0.25488
Train Epoch: 3 [171/1000 5472/32000 (17%)] Loss: 0.28573 batch_time=0.32051
Train Epoch: 3 [176/1000 5632/32000 (18%)] Loss: 0.13074 batch_time=0.20775
Train Epoch: 3 [181/1000 5792/32000 (18%)] Loss: 0.10566 batch_time=0.20218
Train Epoch: 3 [186/1000 5952/32000 (19%)] Loss: 0.10559 batch_time=0.20545
Train Epoch: 3 [191/1000 6112/32000 (19%)] Loss: 0.30603 batch_time=0.20545
Train Epoch: 3 [196/1000 6272/32000 (20%)] Loss: 0.34523 batch_time=0.35131
Train Epoch: 3 [201/1000 6432/32000 (20%)] Loss: 0.24240 batch_time=0.20881
Train Epoch: 3 [206/1000 6592/32000 (21%)] Loss: 0.24371 batch_time=0.21357
Train Epoch: 3 [211/1000 6752/32000 (21%)] Loss: 0.14936 batch_time=0.20676
Train Epoch: 3 [216/1000 6912/32000 (22%)] Loss: 0.18189 batch_time=0.21411
Train Epoch: 3 [221/1000 7072/32000 (22%)] Loss: 0.24817 batch_time=0.22912
Train Epoch: 3 [226/1000 7232/32000 (23%)] Loss: 0.14483 batch_time=0.20613
Train Epoch: 3 [231/1000 7392/32000 (23%)] Loss: 0.17752 batch_time=0.21166
Train Epoch: 3 [236/1000 7552/32000 (24%)] Loss: 0.09133 batch_time=0.24027
Train Epoch: 3 [241/1000 7712/32000 (24%)] Loss: 0.14335 batch_time=0.21397
Train Epoch: 3 [246/1000 7872/32000 (25%)] Loss: 0.16576 batch_time=0.21945
Train Epoch: 3 [251/1000 8032/32000 (25%)] Loss: 0.14702 batch_time=0.21985
Train Epoch: 3 [256/1000 8192/32000 (26%)] Loss: 0.17492 batch_time=0.23614
Train Epoch: 3 [261/1000 8352/32000 (26%)] Loss: 0.25739 batch_time=0.25410
Train Epoch: 3 [266/1000 8512/32000 (27%)] Loss: 0.32244 batch_time=0.20150
Train Epoch: 3 [271/1000 8672/32000 (27%)] Loss: 0.16727 batch_time=0.20803
Train Epoch: 3 [276/1000 8832/32000 (28%)] Loss: 0.13477 batch_time=0.23313
Train Epoch: 3 [281/1000 8992/32000 (28%)] Loss: 0.15064 batch_time=0.40251
Train Epoch: 3 [286/1000 9152/32000 (29%)] Loss: 0.30934 batch_time=0.23224
Train Epoch: 3 [291/1000 9312/32000 (29%)] Loss: 0.24442 batch_time=0.22053
Train Epoch: 3 [296/1000 9472/32000 (30%)] Loss: 0.10249 batch_time=0.20711
Train Epoch: 3 [301/1000 9632/32000 (30%)] Loss: 0.23320 batch_time=0.21201
Train Epoch: 3 [306/1000 9792/32000 (31%)] Loss: 0.11699 batch_time=0.23514
Train Epoch: 3 [311/1000 9952/32000 (31%)] Loss: 0.22317 batch_time=0.23142
Train Epoch: 3 [316/1000 10112/32000 (32%)] Loss: 0.12071 batch_time=0.22064
Train Epoch: 3 [321/1000 10272/32000 (32%)] Loss: 0.24171 batch_time=0.19624
Train Epoch: 3 [326/1000 10432/32000 (33%)] Loss: 0.22804 batch_time=0.19587
Train Epoch: 3 [331/1000 10592/32000 (33%)] Loss: 0.16164 batch_time=0.19610
Train Epoch: 3 [336/1000 10752/32000 (34%)] Loss: 0.19345 batch_time=0.22687
Train Epoch: 3 [341/1000 10912/32000 (34%)] Loss: 0.16319 batch_time=0.27044
Train Epoch: 3 [346/1000 11072/32000 (35%)] Loss: 0.20242 batch_time=0.19908
Train Epoch: 3 [351/1000 11232/32000 (35%)] Loss: 0.06402 batch_time=0.21701
Train Epoch: 3 [356/1000 11392/32000 (36%)] Loss: 0.22754 batch_time=0.20969
Train Epoch: 3 [361/1000 11552/32000 (36%)] Loss: 0.22656 batch_time=0.22227
Train Epoch: 3 [366/1000 11712/32000 (37%)] Loss: 0.12456 batch_time=0.20101
Train Epoch: 3 [371/1000 11872/32000 (37%)] Loss: 0.12171 batch_time=0.20939
Train Epoch: 3 [376/1000 12032/32000 (38%)] Loss: 0.05255 batch_time=0.23405
Train Epoch: 3 [381/1000 12192/32000 (38%)] Loss: 0.09241 batch_time=0.22378
Train Epoch: 3 [386/1000 12352/32000 (39%)] Loss: 0.27480 batch_time=0.23257
Train Epoch: 3 [391/1000 12512/32000 (39%)] Loss: 0.19288 batch_time=0.20469
Train Epoch: 3 [396/1000 12672/32000 (40%)] Loss: 0.32166 batch_time=0.19729
Train Epoch: 3 [401/1000 12832/32000 (40%)] Loss: 0.36690 batch_time=0.27780
Train Epoch: 3 [406/1000 12992/32000 (41%)] Loss: 0.10955 batch_time=0.23446
Train Epoch: 3 [411/1000 13152/32000 (41%)] Loss: 0.33192 batch_time=0.82008
Train Epoch: 3 [416/1000 13312/32000 (42%)] Loss: 0.13002 batch_time=0.21781
Train Epoch: 3 [421/1000 13472/32000 (42%)] Loss: 0.16191 batch_time=0.20388
Train Epoch: 3 [426/1000 13632/32000 (43%)] Loss: 0.27188 batch_time=0.21223
Train Epoch: 3 [431/1000 13792/32000 (43%)] Loss: 0.12113 batch_time=0.21647
Train Epoch: 3 [436/1000 13952/32000 (44%)] Loss: 0.19745 batch_time=0.20765
Train Epoch: 3 [441/1000 14112/32000 (44%)] Loss: 0.10016 batch_time=0.22693
Train Epoch: 3 [446/1000 14272/32000 (45%)] Loss: 0.20440 batch_time=0.20857
Train Epoch: 3 [451/1000 14432/32000 (45%)] Loss: 0.12376 batch_time=0.20187
Train Epoch: 3 [456/1000 14592/32000 (46%)] Loss: 0.21852 batch_time=0.19506
Train Epoch: 3 [461/1000 14752/32000 (46%)] Loss: 0.17515 batch_time=0.19359
Train Epoch: 3 [466/1000 14912/32000 (47%)] Loss: 0.17270 batch_time=0.20250
Train Epoch: 3 [471/1000 15072/32000 (47%)] Loss: 0.19731 batch_time=0.20651
Train Epoch: 3 [476/1000 15232/32000 (48%)] Loss: 0.15955 batch_time=0.21814
Train Epoch: 3 [481/1000 15392/32000 (48%)] Loss: 0.18104 batch_time=0.20628
Train Epoch: 3 [486/1000 15552/32000 (49%)] Loss: 0.27803 batch_time=0.20488
Train Epoch: 3 [491/1000 15712/32000 (49%)] Loss: 0.10713 batch_time=0.32669
Train Epoch: 3 [496/1000 15872/32000 (50%)] Loss: 0.11075 batch_time=0.20237
Train Epoch: 3 [501/1000 16032/32000 (50%)] Loss: 0.14179 batch_time=0.20261
Train Epoch: 3 [506/1000 16192/32000 (51%)] Loss: 0.23555 batch_time=0.23924
Train Epoch: 3 [511/1000 16352/32000 (51%)] Loss: 0.20989 batch_time=0.20448
Train Epoch: 3 [516/1000 16512/32000 (52%)] Loss: 0.23287 batch_time=0.33034
Train Epoch: 3 [521/1000 16672/32000 (52%)] Loss: 0.15301 batch_time=0.19811
Train Epoch: 3 [526/1000 16832/32000 (53%)] Loss: 0.06621 batch_time=0.22468
Train Epoch: 3 [531/1000 16992/32000 (53%)] Loss: 0.13125 batch_time=0.21250
Train Epoch: 3 [536/1000 17152/32000 (54%)] Loss: 0.21950 batch_time=0.22640
Train Epoch: 3 [541/1000 17312/32000 (54%)] Loss: 0.19420 batch_time=0.21269
Train Epoch: 3 [546/1000 17472/32000 (55%)] Loss: 0.24402 batch_time=0.23087
Train Epoch: 3 [551/1000 17632/32000 (55%)] Loss: 0.17590 batch_time=0.23210
Train Epoch: 3 [556/1000 17792/32000 (56%)] Loss: 0.09151 batch_time=0.20351
Train Epoch: 3 [561/1000 17952/32000 (56%)] Loss: 0.09743 batch_time=0.21745
Train Epoch: 3 [566/1000 18112/32000 (57%)] Loss: 0.23933 batch_time=0.23372
Train Epoch: 3 [571/1000 18272/32000 (57%)] Loss: 0.27775 batch_time=0.21213
Train Epoch: 3 [576/1000 18432/32000 (58%)] Loss: 0.07374 batch_time=0.20374
Train Epoch: 3 [581/1000 18592/32000 (58%)] Loss: 0.11455 batch_time=0.23138
Train Epoch: 3 [586/1000 18752/32000 (59%)] Loss: 0.19231 batch_time=0.20453
Train Epoch: 3 [591/1000 18912/32000 (59%)] Loss: 0.05010 batch_time=0.20882
Train Epoch: 3 [596/1000 19072/32000 (60%)] Loss: 0.18689 batch_time=0.21995
Train Epoch: 3 [601/1000 19232/32000 (60%)] Loss: 0.20211 batch_time=0.41857
Train Epoch: 3 [606/1000 19392/32000 (61%)] Loss: 0.08572 batch_time=0.20427
Train Epoch: 3 [611/1000 19552/32000 (61%)] Loss: 0.14875 batch_time=0.20223
Train Epoch: 3 [616/1000 19712/32000 (62%)] Loss: 0.13985 batch_time=0.19173
Train Epoch: 3 [621/1000 19872/32000 (62%)] Loss: 0.20233 batch_time=0.19495
Train Epoch: 3 [626/1000 20032/32000 (63%)] Loss: 0.26289 batch_time=0.19581
Train Epoch: 3 [631/1000 20192/32000 (63%)] Loss: 0.19028 batch_time=0.19959
Train Epoch: 3 [636/1000 20352/32000 (64%)] Loss: 0.39301 batch_time=0.20326
Train Epoch: 3 [641/1000 20512/32000 (64%)] Loss: 0.11200 batch_time=0.20294
Train Epoch: 3 [646/1000 20672/32000 (65%)] Loss: 0.31704 batch_time=0.20528
Train Epoch: 3 [651/1000 20832/32000 (65%)] Loss: 0.13922 batch_time=0.20405
Train Epoch: 3 [656/1000 20992/32000 (66%)] Loss: 0.10487 batch_time=0.25698
Train Epoch: 3 [661/1000 21152/32000 (66%)] Loss: 0.09327 batch_time=0.27432
Train Epoch: 3 [666/1000 21312/32000 (67%)] Loss: 0.25793 batch_time=0.21844
Train Epoch: 3 [671/1000 21472/32000 (67%)] Loss: 0.20077 batch_time=0.21202
Train Epoch: 3 [676/1000 21632/32000 (68%)] Loss: 0.35935 batch_time=0.20267
Train Epoch: 3 [681/1000 21792/32000 (68%)] Loss: 0.09512 batch_time=0.21422
Train Epoch: 3 [686/1000 21952/32000 (69%)] Loss: 0.07223 batch_time=0.19964
Train Epoch: 3 [691/1000 22112/32000 (69%)] Loss: 0.04656 batch_time=0.20059
Train Epoch: 3 [696/1000 22272/32000 (70%)] Loss: 0.25299 batch_time=0.20381
Train Epoch: 3 [701/1000 22432/32000 (70%)] Loss: 0.26719 batch_time=0.21478
Train Epoch: 3 [706/1000 22592/32000 (71%)] Loss: 0.11133 batch_time=0.23683
Train Epoch: 3 [711/1000 22752/32000 (71%)] Loss: 0.22902 batch_time=0.23834
Train Epoch: 3 [716/1000 22912/32000 (72%)] Loss: 0.21175 batch_time=0.22385
Train Epoch: 3 [721/1000 23072/32000 (72%)] Loss: 0.17661 batch_time=0.31281
Train Epoch: 3 [726/1000 23232/32000 (73%)] Loss: 0.07526 batch_time=0.22755
Train Epoch: 3 [731/1000 23392/32000 (73%)] Loss: 0.11827 batch_time=0.75336
Train Epoch: 3 [736/1000 23552/32000 (74%)] Loss: 0.12108 batch_time=0.21033
Train Epoch: 3 [741/1000 23712/32000 (74%)] Loss: 0.12597 batch_time=0.23620
Train Epoch: 3 [746/1000 23872/32000 (75%)] Loss: 0.10222 batch_time=0.20487
Train Epoch: 3 [751/1000 24032/32000 (75%)] Loss: 0.18159 batch_time=0.21313
Train Epoch: 3 [756/1000 24192/32000 (76%)] Loss: 0.14434 batch_time=0.19435
Train Epoch: 3 [761/1000 24352/32000 (76%)] Loss: 0.37953 batch_time=0.20012
Train Epoch: 3 [766/1000 24512/32000 (77%)] Loss: 0.15682 batch_time=0.21322
Train Epoch: 3 [771/1000 24672/32000 (77%)] Loss: 0.35769 batch_time=0.19788
Train Epoch: 3 [776/1000 24832/32000 (78%)] Loss: 0.06715 batch_time=0.19602
Train Epoch: 3 [781/1000 24992/32000 (78%)] Loss: 0.32597 batch_time=0.19468
Train Epoch: 3 [786/1000 25152/32000 (79%)] Loss: 0.08681 batch_time=0.19538
Train Epoch: 3 [791/1000 25312/32000 (79%)] Loss: 0.16265 batch_time=0.19884
Train Epoch: 3 [796/1000 25472/32000 (80%)] Loss: 0.20815 batch_time=0.19196
Train Epoch: 3 [801/1000 25632/32000 (80%)] Loss: 0.08542 batch_time=0.19598
Train Epoch: 3 [806/1000 25792/32000 (81%)] Loss: 0.30487 batch_time=0.19402
Train Epoch: 3 [811/1000 25952/32000 (81%)] Loss: 0.17147 batch_time=0.34902
Train Epoch: 3 [816/1000 26112/32000 (82%)] Loss: 0.15223 batch_time=0.19711
Train Epoch: 3 [821/1000 26272/32000 (82%)] Loss: 0.14433 batch_time=0.20421
Train Epoch: 3 [826/1000 26432/32000 (83%)] Loss: 0.08178 batch_time=0.19730
Train Epoch: 3 [831/1000 26592/32000 (83%)] Loss: 0.08658 batch_time=0.19792
Train Epoch: 3 [836/1000 26752/32000 (84%)] Loss: 0.16652 batch_time=0.30522
Train Epoch: 3 [841/1000 26912/32000 (84%)] Loss: 0.13576 batch_time=0.19381
Train Epoch: 3 [846/1000 27072/32000 (85%)] Loss: 0.05952 batch_time=0.19672
Train Epoch: 3 [851/1000 27232/32000 (85%)] Loss: 0.14568 batch_time=0.20342
Train Epoch: 3 [856/1000 27392/32000 (86%)] Loss: 0.17455 batch_time=0.20088
Train Epoch: 3 [861/1000 27552/32000 (86%)] Loss: 0.21370 batch_time=0.19438
Train Epoch: 3 [866/1000 27712/32000 (87%)] Loss: 0.15607 batch_time=0.19868
Train Epoch: 3 [871/1000 27872/32000 (87%)] Loss: 0.09883 batch_time=0.21497
Train Epoch: 3 [876/1000 28032/32000 (88%)] Loss: 0.12553 batch_time=0.20027
Train Epoch: 3 [881/1000 28192/32000 (88%)] Loss: 0.18391 batch_time=0.19732
Train Epoch: 3 [886/1000 28352/32000 (89%)] Loss: 0.12233 batch_time=0.20801
Train Epoch: 3 [891/1000 28512/32000 (89%)] Loss: 0.09355 batch_time=0.19711
Train Epoch: 3 [896/1000 28672/32000 (90%)] Loss: 0.16021 batch_time=0.19868
Train Epoch: 3 [901/1000 28832/32000 (90%)] Loss: 0.22809 batch_time=0.25764
Train Epoch: 3 [906/1000 28992/32000 (91%)] Loss: 0.09255 batch_time=0.19683
Train Epoch: 3 [911/1000 29152/32000 (91%)] Loss: 0.24003 batch_time=0.20780
Train Epoch: 3 [916/1000 29312/32000 (92%)] Loss: 0.29422 batch_time=0.21298
Train Epoch: 3 [921/1000 29472/32000 (92%)] Loss: 0.14332 batch_time=0.41568
Train Epoch: 3 [926/1000 29632/32000 (93%)] Loss: 0.21401 batch_time=0.19524
Train Epoch: 3 [931/1000 29792/32000 (93%)] Loss: 0.11016 batch_time=0.20231
Train Epoch: 3 [936/1000 29952/32000 (94%)] Loss: 0.06276 batch_time=0.20084
Train Epoch: 3 [941/1000 30112/32000 (94%)] Loss: 0.06368 batch_time=0.19839
Train Epoch: 3 [946/1000 30272/32000 (95%)] Loss: 0.09511 batch_time=0.19732
Train Epoch: 3 [951/1000 30432/32000 (95%)] Loss: 0.24384 batch_time=0.21457
Train Epoch: 3 [956/1000 30592/32000 (96%)] Loss: 0.06595 batch_time=0.20240
Train Epoch: 3 [961/1000 30752/32000 (96%)] Loss: 0.13270 batch_time=0.19591
Train Epoch: 3 [966/1000 30912/32000 (97%)] Loss: 0.39923 batch_time=0.19893
Train Epoch: 3 [971/1000 31072/32000 (97%)] Loss: 0.12685 batch_time=0.19714
Train Epoch: 3 [976/1000 31232/32000 (98%)] Loss: 0.26288 batch_time=0.25443
Train Epoch: 3 [981/1000 31392/32000 (98%)] Loss: 0.17102 batch_time=0.27051
Train Epoch: 3 [986/1000 31552/32000 (99%)] Loss: 0.09937 batch_time=0.19869
Train Epoch: 3 [991/1000 31712/32000 (99%)] Loss: 0.13063 batch_time=0.24405
Train Epoch: 3 [996/1000 31872/32000 (100%)] Loss: 0.21245 batch_time=0.21124
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch3.pth ...
Done in 3.791s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch3.pth ...
Done in 7.471s
removing stale ckpt [epoch 2] [took 0.01s]
epoch : 3
loss : 0.17951207614690065
learning_rate : 4.25e-05
n_samples : 96000
n_steps : 3000
ActivityNet_val1_test/t2v_metrics/R1: 18.03945495220663
ActivityNet_val1_test/t2v_metrics/R5: 48.38316046369738
ActivityNet_val1_test/t2v_metrics/R10: 64.6329062436445
ActivityNet_val1_test/t2v_metrics/R50: 92.59711206019931
ActivityNet_val1_test/t2v_metrics/MedR: 6.0
ActivityNet_val1_test/t2v_metrics/MeanR: 22.754525116941224
ActivityNet_val1_test/t2v_metrics/geometric_mean_R1-R5-R10: 38.35221429062897
ActivityNet_val1_test/v2t_metrics/R1: 18.364856619890176
ActivityNet_val1_test/v2t_metrics/R5: 48.56619890176937
ActivityNet_val1_test/v2t_metrics/R10: 65.71079926784624
ActivityNet_val1_test/v2t_metrics/R50: 92.55643685173887
ActivityNet_val1_test/v2t_metrics/MedR: 6.0
ActivityNet_val1_test/v2t_metrics/MeanR: 23.2749644091926
ActivityNet_val1_test/v2t_metrics/geometric_mean_R1-R5-R10: 38.84359958886831
mnt_best : 38.35221429062897
not_improved_count: 0
Train Epoch: 4 [1/1000 32/32000 (0%)] Loss: 0.11830 batch_time=21.79460
Train Epoch: 4 [6/1000 192/32000 (1%)] Loss: 0.19437 batch_time=0.30893
Train Epoch: 4 [11/1000 352/32000 (1%)] Loss: 0.18216 batch_time=0.19606
Train Epoch: 4 [16/1000 512/32000 (2%)] Loss: 0.20051 batch_time=0.23118
Train Epoch: 4 [21/1000 672/32000 (2%)] Loss: 0.32754 batch_time=0.19648
Train Epoch: 4 [26/1000 832/32000 (3%)] Loss: 0.09211 batch_time=0.19403
Train Epoch: 4 [31/1000 992/32000 (3%)] Loss: 0.25002 batch_time=0.21918
Train Epoch: 4 [36/1000 1152/32000 (4%)] Loss: 0.07363 batch_time=0.21387
Train Epoch: 4 [41/1000 1312/32000 (4%)] Loss: 0.25117 batch_time=0.21258
Train Epoch: 4 [46/1000 1472/32000 (5%)] Loss: 0.22959 batch_time=0.19854
Train Epoch: 4 [51/1000 1632/32000 (5%)] Loss: 0.11769 batch_time=0.19656
Train Epoch: 4 [56/1000 1792/32000 (6%)] Loss: 0.37682 batch_time=0.19566
Train Epoch: 4 [61/1000 1952/32000 (6%)] Loss: 0.05273 batch_time=0.19606
Train Epoch: 4 [66/1000 2112/32000 (7%)] Loss: 0.12687 batch_time=0.19758
Train Epoch: 4 [71/1000 2272/32000 (7%)] Loss: 0.04841 batch_time=0.19899
Train Epoch: 4 [76/1000 2432/32000 (8%)] Loss: 0.08383 batch_time=0.19551
Train Epoch: 4 [81/1000 2592/32000 (8%)] Loss: 0.28394 batch_time=0.31990
Train Epoch: 4 [86/1000 2752/32000 (9%)] Loss: 0.18277 batch_time=0.19750
Train Epoch: 4 [91/1000 2912/32000 (9%)] Loss: 0.07101 batch_time=0.19805
Train Epoch: 4 [96/1000 3072/32000 (10%)] Loss: 0.05385 batch_time=0.19758
Train Epoch: 4 [101/1000 3232/32000 (10%)] Loss: 0.04974 batch_time=0.21058
Train Epoch: 4 [106/1000 3392/32000 (11%)] Loss: 0.07697 batch_time=0.19735
Train Epoch: 4 [111/1000 3552/32000 (11%)] Loss: 0.27239 batch_time=0.20124
Train Epoch: 4 [116/1000 3712/32000 (12%)] Loss: 0.10491 batch_time=0.20027
Train Epoch: 4 [121/1000 3872/32000 (12%)] Loss: 0.18125 batch_time=0.31367
Train Epoch: 4 [126/1000 4032/32000 (13%)] Loss: 0.18273 batch_time=0.19555
Train Epoch: 4 [131/1000 4192/32000 (13%)] Loss: 0.15672 batch_time=0.26766
Train Epoch: 4 [136/1000 4352/32000 (14%)] Loss: 0.16660 batch_time=0.21183
Train Epoch: 4 [141/1000 4512/32000 (14%)] Loss: 0.19636 batch_time=0.20663
Train Epoch: 4 [146/1000 4672/32000 (15%)] Loss: 0.14316 batch_time=0.44271
Train Epoch: 4 [151/1000 4832/32000 (15%)] Loss: 0.23533 batch_time=0.19855
Train Epoch: 4 [156/1000 4992/32000 (16%)] Loss: 0.06123 batch_time=0.19604
Train Epoch: 4 [161/1000 5152/32000 (16%)] Loss: 0.10462 batch_time=0.23148
Train Epoch: 4 [166/1000 5312/32000 (17%)] Loss: 0.13591 batch_time=0.19268
Train Epoch: 4 [171/1000 5472/32000 (17%)] Loss: 0.09899 batch_time=0.19585
Train Epoch: 4 [176/1000 5632/32000 (18%)] Loss: 0.06389 batch_time=0.19873
Train Epoch: 4 [181/1000 5792/32000 (18%)] Loss: 0.07523 batch_time=0.19507
Train Epoch: 4 [186/1000 5952/32000 (19%)] Loss: 0.15260 batch_time=0.19627
Train Epoch: 4 [191/1000 6112/32000 (19%)] Loss: 0.06217 batch_time=0.19651
Train Epoch: 4 [196/1000 6272/32000 (20%)] Loss: 0.17277 batch_time=0.21057
Train Epoch: 4 [201/1000 6432/32000 (20%)] Loss: 0.12584 batch_time=0.19755
Train Epoch: 4 [206/1000 6592/32000 (21%)] Loss: 0.39843 batch_time=0.19769
Train Epoch: 4 [211/1000 6752/32000 (21%)] Loss: 0.07727 batch_time=0.20328
Train Epoch: 4 [216/1000 6912/32000 (22%)] Loss: 0.23350 batch_time=0.20781
Train Epoch: 4 [221/1000 7072/32000 (22%)] Loss: 0.11224 batch_time=0.20064
Train Epoch: 4 [226/1000 7232/32000 (23%)] Loss: 0.18095 batch_time=0.19777
Train Epoch: 4 [231/1000 7392/32000 (23%)] Loss: 0.16253 batch_time=0.53426
Train Epoch: 4 [236/1000 7552/32000 (24%)] Loss: 0.16799 batch_time=0.23112
Train Epoch: 4 [241/1000 7712/32000 (24%)] Loss: 0.07988 batch_time=0.20542
Train Epoch: 4 [246/1000 7872/32000 (25%)] Loss: 0.16906 batch_time=0.23173
Train Epoch: 4 [251/1000 8032/32000 (25%)] Loss: 0.20925 batch_time=0.20040
Train Epoch: 4 [256/1000 8192/32000 (26%)] Loss: 0.14338 batch_time=0.22577
Train Epoch: 4 [261/1000 8352/32000 (26%)] Loss: 0.13625 batch_time=0.19818
Train Epoch: 4 [266/1000 8512/32000 (27%)] Loss: 0.19122 batch_time=0.19662
Train Epoch: 4 [271/1000 8672/32000 (27%)] Loss: 0.18259 batch_time=0.19762
Train Epoch: 4 [276/1000 8832/32000 (28%)] Loss: 0.08585 batch_time=0.20093
Train Epoch: 4 [281/1000 8992/32000 (28%)] Loss: 0.09247 batch_time=0.19639
Train Epoch: 4 [286/1000 9152/32000 (29%)] Loss: 0.20611 batch_time=0.19778
Train Epoch: 4 [291/1000 9312/32000 (29%)] Loss: 0.14507 batch_time=0.19874
Train Epoch: 4 [296/1000 9472/32000 (30%)] Loss: 0.26630 batch_time=0.19512
Train Epoch: 4 [301/1000 9632/32000 (30%)] Loss: 0.09668 batch_time=0.19854
Train Epoch: 4 [306/1000 9792/32000 (31%)] Loss: 0.13357 batch_time=0.22112
Train Epoch: 4 [311/1000 9952/32000 (31%)] Loss: 0.09399 batch_time=0.19724
Train Epoch: 4 [316/1000 10112/32000 (32%)] Loss: 0.17619 batch_time=0.20743
Train Epoch: 4 [321/1000 10272/32000 (32%)] Loss: 0.26778 batch_time=0.20971
Train Epoch: 4 [326/1000 10432/32000 (33%)] Loss: 0.09406 batch_time=0.27699
Train Epoch: 4 [331/1000 10592/32000 (33%)] Loss: 0.17091 batch_time=0.19666
Train Epoch: 4 [336/1000 10752/32000 (34%)] Loss: 0.09119 batch_time=0.22780
Train Epoch: 4 [341/1000 10912/32000 (34%)] Loss: 0.10522 batch_time=0.21055
Train Epoch: 4 [346/1000 11072/32000 (35%)] Loss: 0.09495 batch_time=0.19764
Train Epoch: 4 [351/1000 11232/32000 (35%)] Loss: 0.41696 batch_time=0.19635
Train Epoch: 4 [356/1000 11392/32000 (36%)] Loss: 0.15851 batch_time=0.20159
Train Epoch: 4 [361/1000 11552/32000 (36%)] Loss: 0.14935 batch_time=0.19527
Train Epoch: 4 [366/1000 11712/32000 (37%)] Loss: 0.06729 batch_time=0.19398
Train Epoch: 4 [371/1000 11872/32000 (37%)] Loss: 0.16778 batch_time=0.19487
Train Epoch: 4 [376/1000 12032/32000 (38%)] Loss: 0.15733 batch_time=0.19858
Train Epoch: 4 [381/1000 12192/32000 (38%)] Loss: 0.18536 batch_time=0.21352
Train Epoch: 4 [386/1000 12352/32000 (39%)] Loss: 0.24012 batch_time=0.20129
Train Epoch: 4 [391/1000 12512/32000 (39%)] Loss: 0.06099 batch_time=0.19354
Train Epoch: 4 [396/1000 12672/32000 (40%)] Loss: 0.10405 batch_time=0.19818
Train Epoch: 4 [401/1000 12832/32000 (40%)] Loss: 0.17758 batch_time=0.30710
Train Epoch: 4 [406/1000 12992/32000 (41%)] Loss: 0.24006 batch_time=0.20631
Train Epoch: 4 [411/1000 13152/32000 (41%)] Loss: 0.12032 batch_time=0.20632
Train Epoch: 4 [416/1000 13312/32000 (42%)] Loss: 0.13607 batch_time=0.19493
Train Epoch: 4 [421/1000 13472/32000 (42%)] Loss: 0.09458 batch_time=0.47022
Train Epoch: 4 [426/1000 13632/32000 (43%)] Loss: 0.25975 batch_time=0.19606
Train Epoch: 4 [431/1000 13792/32000 (43%)] Loss: 0.44486 batch_time=0.19483
Train Epoch: 4 [436/1000 13952/32000 (44%)] Loss: 0.15541 batch_time=0.19222
Train Epoch: 4 [441/1000 14112/32000 (44%)] Loss: 0.07713 batch_time=0.30699
Train Epoch: 4 [446/1000 14272/32000 (45%)] Loss: 0.33211 batch_time=0.20226
Train Epoch: 4 [451/1000 14432/32000 (45%)] Loss: 0.10098 batch_time=0.26093
Train Epoch: 4 [456/1000 14592/32000 (46%)] Loss: 0.09169 batch_time=0.19735
Train Epoch: 4 [461/1000 14752/32000 (46%)] Loss: 0.17494 batch_time=0.19689
Train Epoch: 4 [466/1000 14912/32000 (47%)] Loss: 0.10128 batch_time=0.40865
Train Epoch: 4 [471/1000 15072/32000 (47%)] Loss: 0.18841 batch_time=0.19478
Train Epoch: 4 [476/1000 15232/32000 (48%)] Loss: 0.21523 batch_time=0.19838
Train Epoch: 4 [481/1000 15392/32000 (48%)] Loss: 0.06371 batch_time=0.23897
Train Epoch: 4 [486/1000 15552/32000 (49%)] Loss: 0.18103 batch_time=0.20840
Train Epoch: 4 [491/1000 15712/32000 (49%)] Loss: 0.12246 batch_time=0.20151
Train Epoch: 4 [496/1000 15872/32000 (50%)] Loss: 0.32658 batch_time=0.20298
Train Epoch: 4 [501/1000 16032/32000 (50%)] Loss: 0.11728 batch_time=0.19630
Train Epoch: 4 [506/1000 16192/32000 (51%)] Loss: 0.13983 batch_time=0.19850
Train Epoch: 4 [511/1000 16352/32000 (51%)] Loss: 0.23349 batch_time=0.19551
Train Epoch: 4 [516/1000 16512/32000 (52%)] Loss: 0.10447 batch_time=0.21084
Train Epoch: 4 [521/1000 16672/32000 (52%)] Loss: 0.14911 batch_time=0.19896
Train Epoch: 4 [526/1000 16832/32000 (53%)] Loss: 0.08667 batch_time=0.19593
Train Epoch: 4 [531/1000 16992/32000 (53%)] Loss: 0.13997 batch_time=0.19596
Train Epoch: 4 [536/1000 17152/32000 (54%)] Loss: 0.11799 batch_time=0.19847
Train Epoch: 4 [541/1000 17312/32000 (54%)] Loss: 0.04614 batch_time=0.19687
Train Epoch: 4 [546/1000 17472/32000 (55%)] Loss: 0.11992 batch_time=0.19946
Train Epoch: 4 [551/1000 17632/32000 (55%)] Loss: 0.24513 batch_time=0.56121
Train Epoch: 4 [556/1000 17792/32000 (56%)] Loss: 0.23135 batch_time=0.21415
Train Epoch: 4 [561/1000 17952/32000 (56%)] Loss: 0.09513 batch_time=0.19556
Train Epoch: 4 [566/1000 18112/32000 (57%)] Loss: 0.18192 batch_time=0.19694
Train Epoch: 4 [571/1000 18272/32000 (57%)] Loss: 0.17206 batch_time=0.19665
Train Epoch: 4 [576/1000 18432/32000 (58%)] Loss: 0.14948 batch_time=0.22030
Train Epoch: 4 [581/1000 18592/32000 (58%)] Loss: 0.19165 batch_time=0.19703
Train Epoch: 4 [586/1000 18752/32000 (59%)] Loss: 0.16196 batch_time=0.19699
Train Epoch: 4 [591/1000 18912/32000 (59%)] Loss: 0.10642 batch_time=0.19790
Train Epoch: 4 [596/1000 19072/32000 (60%)] Loss: 0.07301 batch_time=0.19825
Train Epoch: 4 [601/1000 19232/32000 (60%)] Loss: 0.08942 batch_time=0.19784
Train Epoch: 4 [606/1000 19392/32000 (61%)] Loss: 0.02331 batch_time=0.19661
Train Epoch: 4 [611/1000 19552/32000 (61%)] Loss: 0.14227 batch_time=0.19585
Train Epoch: 4 [616/1000 19712/32000 (62%)] Loss: 0.17195 batch_time=0.19928
Train Epoch: 4 [621/1000 19872/32000 (62%)] Loss: 0.17838 batch_time=0.19941
Train Epoch: 4 [626/1000 20032/32000 (63%)] Loss: 0.36241 batch_time=0.19768
Train Epoch: 4 [631/1000 20192/32000 (63%)] Loss: 0.09215 batch_time=0.19922
Train Epoch: 4 [636/1000 20352/32000 (64%)] Loss: 0.22392 batch_time=0.21081
Train Epoch: 4 [641/1000 20512/32000 (64%)] Loss: 0.09854 batch_time=0.19933
Train Epoch: 4 [646/1000 20672/32000 (65%)] Loss: 0.08489 batch_time=0.28551
Train Epoch: 4 [651/1000 20832/32000 (65%)] Loss: 0.12102 batch_time=0.21178
Train Epoch: 4 [656/1000 20992/32000 (66%)] Loss: 0.05267 batch_time=0.23117
Train Epoch: 4 [661/1000 21152/32000 (66%)] Loss: 0.23477 batch_time=0.21667
Train Epoch: 4 [666/1000 21312/32000 (67%)] Loss: 0.13997 batch_time=0.19744
Train Epoch: 4 [671/1000 21472/32000 (67%)] Loss: 0.09260 batch_time=0.21041
Train Epoch: 4 [676/1000 21632/32000 (68%)] Loss: 0.11730 batch_time=0.19731
Train Epoch: 4 [681/1000 21792/32000 (68%)] Loss: 0.29563 batch_time=0.19879
Train Epoch: 4 [686/1000 21952/32000 (69%)] Loss: 0.15424 batch_time=0.19817
Train Epoch: 4 [691/1000 22112/32000 (69%)] Loss: 0.15729 batch_time=0.19664
Train Epoch: 4 [696/1000 22272/32000 (70%)] Loss: 0.13098 batch_time=0.19912
Train Epoch: 4 [701/1000 22432/32000 (70%)] Loss: 0.07027 batch_time=0.19590
Train Epoch: 4 [706/1000 22592/32000 (71%)] Loss: 0.04183 batch_time=0.19782
Train Epoch: 4 [711/1000 22752/32000 (71%)] Loss: 0.16164 batch_time=0.19905
Train Epoch: 4 [716/1000 22912/32000 (72%)] Loss: 0.16844 batch_time=0.20378
Train Epoch: 4 [721/1000 23072/32000 (72%)] Loss: 0.11278 batch_time=0.31492
Train Epoch: 4 [726/1000 23232/32000 (73%)] Loss: 0.05859 batch_time=0.19648
Train Epoch: 4 [731/1000 23392/32000 (73%)] Loss: 0.11957 batch_time=0.19849
Train Epoch: 4 [736/1000 23552/32000 (74%)] Loss: 0.09720 batch_time=0.19408
Train Epoch: 4 [741/1000 23712/32000 (74%)] Loss: 0.08235 batch_time=0.19318
Train Epoch: 4 [746/1000 23872/32000 (75%)] Loss: 0.19145 batch_time=0.19494
Train Epoch: 4 [751/1000 24032/32000 (75%)] Loss: 0.25272 batch_time=0.19412
Train Epoch: 4 [756/1000 24192/32000 (76%)] Loss: 0.20952 batch_time=0.19835
Train Epoch: 4 [761/1000 24352/32000 (76%)] Loss: 0.07813 batch_time=0.32133
Train Epoch: 4 [766/1000 24512/32000 (77%)] Loss: 0.04227 batch_time=0.20217
Train Epoch: 4 [771/1000 24672/32000 (77%)] Loss: 0.21913 batch_time=0.28733
Train Epoch: 4 [776/1000 24832/32000 (78%)] Loss: 0.17426 batch_time=0.19799
Train Epoch: 4 [781/1000 24992/32000 (78%)] Loss: 0.08789 batch_time=0.19849
Train Epoch: 4 [786/1000 25152/32000 (79%)] Loss: 0.06542 batch_time=0.41468
Train Epoch: 4 [791/1000 25312/32000 (79%)] Loss: 0.07804 batch_time=0.19686
Train Epoch: 4 [796/1000 25472/32000 (80%)] Loss: 0.08959 batch_time=0.19511
Train Epoch: 4 [801/1000 25632/32000 (80%)] Loss: 0.25560 batch_time=0.22873
Train Epoch: 4 [806/1000 25792/32000 (81%)] Loss: 0.20301 batch_time=0.19471
Train Epoch: 4 [811/1000 25952/32000 (81%)] Loss: 0.08781 batch_time=0.19723
Train Epoch: 4 [816/1000 26112/32000 (82%)] Loss: 0.13877 batch_time=0.19607
Train Epoch: 4 [821/1000 26272/32000 (82%)] Loss: 0.05689 batch_time=0.20987
Train Epoch: 4 [826/1000 26432/32000 (83%)] Loss: 0.11159 batch_time=0.20699
Train Epoch: 4 [831/1000 26592/32000 (83%)] Loss: 0.27679 batch_time=0.19718
Train Epoch: 4 [836/1000 26752/32000 (84%)] Loss: 0.11238 batch_time=0.21489
Train Epoch: 4 [841/1000 26912/32000 (84%)] Loss: 0.16477 batch_time=0.21940
Train Epoch: 4 [846/1000 27072/32000 (85%)] Loss: 0.23315 batch_time=0.19919
Train Epoch: 4 [851/1000 27232/32000 (85%)] Loss: 0.04748 batch_time=0.19746
Train Epoch: 4 [856/1000 27392/32000 (86%)] Loss: 0.13132 batch_time=0.20340
Train Epoch: 4 [861/1000 27552/32000 (86%)] Loss: 0.30364 batch_time=0.19810
Train Epoch: 4 [866/1000 27712/32000 (87%)] Loss: 0.10279 batch_time=0.19976
Train Epoch: 4 [871/1000 27872/32000 (87%)] Loss: 0.19723 batch_time=0.53932
Train Epoch: 4 [876/1000 28032/32000 (88%)] Loss: 0.13777 batch_time=0.21291
Train Epoch: 4 [881/1000 28192/32000 (88%)] Loss: 0.17136 batch_time=0.19815
Train Epoch: 4 [886/1000 28352/32000 (89%)] Loss: 0.24053 batch_time=0.19671
Train Epoch: 4 [891/1000 28512/32000 (89%)] Loss: 0.14930 batch_time=0.19844
Train Epoch: 4 [896/1000 28672/32000 (90%)] Loss: 0.11831 batch_time=0.21582
Train Epoch: 4 [901/1000 28832/32000 (90%)] Loss: 0.10950 batch_time=0.20716
Train Epoch: 4 [906/1000 28992/32000 (91%)] Loss: 0.20750 batch_time=0.19946
Train Epoch: 4 [911/1000 29152/32000 (91%)] Loss: 0.07947 batch_time=0.19999
Train Epoch: 4 [916/1000 29312/32000 (92%)] Loss: 0.06395 batch_time=0.20249
Train Epoch: 4 [921/1000 29472/32000 (92%)] Loss: 0.18547 batch_time=0.21095
Train Epoch: 4 [926/1000 29632/32000 (93%)] Loss: 0.14469 batch_time=0.20201
Train Epoch: 4 [931/1000 29792/32000 (93%)] Loss: 0.26335 batch_time=0.19712
Train Epoch: 4 [936/1000 29952/32000 (94%)] Loss: 0.19215 batch_time=0.19791
Train Epoch: 4 [941/1000 30112/32000 (94%)] Loss: 0.13305 batch_time=0.20733
Train Epoch: 4 [946/1000 30272/32000 (95%)] Loss: 0.23368 batch_time=0.19933
Train Epoch: 4 [951/1000 30432/32000 (95%)] Loss: 0.10243 batch_time=0.20515
Train Epoch: 4 [956/1000 30592/32000 (96%)] Loss: 0.15595 batch_time=0.21043
Train Epoch: 4 [961/1000 30752/32000 (96%)] Loss: 0.09728 batch_time=0.19936
Train Epoch: 4 [966/1000 30912/32000 (97%)] Loss: 0.17828 batch_time=0.27926
Train Epoch: 4 [971/1000 31072/32000 (97%)] Loss: 0.24820 batch_time=0.19863
Train Epoch: 4 [976/1000 31232/32000 (98%)] Loss: 0.07748 batch_time=0.22925
Train Epoch: 4 [981/1000 31392/32000 (98%)] Loss: 0.05570 batch_time=0.19751
Train Epoch: 4 [986/1000 31552/32000 (99%)] Loss: 0.05100 batch_time=0.19615
Train Epoch: 4 [991/1000 31712/32000 (99%)] Loss: 0.07563 batch_time=0.19935
Train Epoch: 4 [996/1000 31872/32000 (100%)] Loss: 0.13433 batch_time=0.19550
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch4.pth ...
Done in 15.764s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/HCT_ActivityNet/checkpoint-epoch4.pth ...
Done in 19.547s
removing stale ckpt [epoch 3] [took 0.01s]
epoch : 4
loss : 0.14900054701790214
learning_rate : 4.25e-05
n_samples : 128000
n_steps : 4000
ActivityNet_val1_test/t2v_metrics/R1: 18.446207036811064
ActivityNet_val1_test/t2v_metrics/R5: 49.4407158836689
ActivityNet_val1_test/t2v_metrics/R10: 65.62944885092536
ActivityNet_val1_test/t2v_metrics/R50: 92.80048810250153
ActivityNet_val1_test/t2v_metrics/MedR: 6.0
ActivityNet_val1_test/t2v_metrics/MeanR: 22.489322757779135
ActivityNet_val1_test/t2v_metrics/geometric_mean_R1-R5-R10: 39.11681884807137
ActivityNet_val1_test/v2t_metrics/R1: 20.45962985560301
ActivityNet_val1_test/v2t_metrics/R5: 50.19320724018711
ActivityNet_val1_test/v2t_metrics/R10: 66.56497864551555
ActivityNet_val1_test/v2t_metrics/R50: 93.30892820825707
ActivityNet_val1_test/v2t_metrics/MedR: 5.0
ActivityNet_val1_test/v2t_metrics/MeanR: 21.526032133414684
ActivityNet_val1_test/v2t_metrics/geometric_mean_R1-R5-R10: 40.88802864228116
mnt_best : 39.11681884807137
not_improved_count: 0
Train Epoch: 5 [1/1000 32/32000 (0%)] Loss: 0.07605 batch_time=24.69522
Train Epoch: 5 [6/1000 192/32000 (1%)] Loss: 0.13747 batch_time=0.19753
Train Epoch: 5 [11/1000 352/32000 (1%)] Loss: 0.18166 batch_time=0.19923
Train Epoch: 5 [16/1000 512/32000 (2%)] Loss: 0.14235 batch_time=0.21544
Train Epoch: 5 [21/1000 672/32000 (2%)] Loss: 0.08494 batch_time=0.19894
Train Epoch: 5 [26/1000 832/32000 (3%)] Loss: 0.14369 batch_time=0.96504
Train Epoch: 5 [31/1000 992/32000 (3%)] Loss: 0.08540 batch_time=0.19893
Train Epoch: 5 [36/1000 1152/32000 (4%)] Loss: 0.13944 batch_time=0.20332
Train Epoch: 5 [41/1000 1312/32000 (4%)] Loss: 0.07911 batch_time=0.20922
Train Epoch: 5 [46/1000 1472/32000 (5%)] Loss: 0.24075 batch_time=0.21021
Train Epoch: 5 [51/1000 1632/32000 (5%)] Loss: 0.06026 batch_time=0.19957
Train Epoch: 5 [56/1000 1792/32000 (6%)] Loss: 0.10571 batch_time=0.20661
Train Epoch: 5 [61/1000 1952/32000 (6%)] Loss: 0.17785 batch_time=0.20930
Train Epoch: 5 [66/1000 2112/32000 (7%)] Loss: 0.16210 batch_time=0.43897
Train Epoch: 5 [71/1000 2272/32000 (7%)] Loss: 0.17215 batch_time=0.22369
Train Epoch: 5 [76/1000 2432/32000 (8%)] Loss: 0.10369 batch_time=0.21204
Train Epoch: 5 [81/1000 2592/32000 (8%)] Loss: 0.05598 batch_time=0.21669
Train Epoch: 5 [86/1000 2752/32000 (9%)] Loss: 0.04953 batch_time=0.22782
Train Epoch: 5 [91/1000 2912/32000 (9%)] Loss: 0.03271 batch_time=0.21162
Train Epoch: 5 [96/1000 3072/32000 (10%)] Loss: 0.02100 batch_time=0.21157
Train Epoch: 5 [101/1000 3232/32000 (10%)] Loss: 0.09721 batch_time=0.21846
Train Epoch: 5 [106/1000 3392/32000 (11%)] Loss: 0.09621 batch_time=0.19997
Train Epoch: 5 [111/1000 3552/32000 (11%)] Loss: 0.09628 batch_time=0.19829
Train Epoch: 5 [116/1000 3712/32000 (12%)] Loss: 0.07417 batch_time=0.21155
Train Epoch: 5 [121/1000 3872/32000 (12%)] Loss: 0.05569 batch_time=0.21729
Train Epoch: 5 [126/1000 4032/32000 (13%)] Loss: 0.05002 batch_time=0.21203
Train Epoch: 5 [131/1000 4192/32000 (13%)] Loss: 0.12386 batch_time=0.20318
Train Epoch: 5 [136/1000 4352/32000 (14%)] Loss: 0.08296 batch_time=0.21826
Train Epoch: 5 [141/1000 4512/32000 (14%)] Loss: 0.07893 batch_time=0.21642
Train Epoch: 5 [146/1000 4672/32000 (15%)] Loss: 0.14918 batch_time=0.28922
Train Epoch: 5 [151/1000 4832/32000 (15%)] Loss: 0.13392 batch_time=0.21560
Train Epoch: 5 [156/1000 4992/32000 (16%)] Loss: 0.07731 batch_time=0.22918
Train Epoch: 5 [161/1000 5152/32000 (16%)] Loss: 0.24887 batch_time=0.21613
Train Epoch: 5 [166/1000 5312/32000 (17%)] Loss: 0.11492 batch_time=0.21211
Train Epoch: 5 [171/1000 5472/32000 (17%)] Loss: 0.12616 batch_time=0.20717
Train Epoch: 5 [176/1000 5632/32000 (18%)] Loss: 0.19497 batch_time=0.19847
Train Epoch: 5 [181/1000 5792/32000 (18%)] Loss: 0.17602 batch_time=0.22000
Train Epoch: 5 [186/1000 5952/32000 (19%)] Loss: 0.07006 batch_time=0.22918
Train Epoch: 5 [191/1000 6112/32000 (19%)] Loss: 0.11009 batch_time=0.19791
Train Epoch: 5 [196/1000 6272/32000 (20%)] Loss: 0.15920 batch_time=0.23687
Train Epoch: 5 [201/1000 6432/32000 (20%)] Loss: 0.21024 batch_time=0.21201
Train Epoch: 5 [206/1000 6592/32000 (21%)] Loss: 0.14793 batch_time=0.20279
Train Epoch: 5 [211/1000 6752/32000 (21%)] Loss: 0.06724 batch_time=0.20039
Train Epoch: 5 [216/1000 6912/32000 (22%)] Loss: 0.28003 batch_time=0.31000
Train Epoch: 5 [221/1000 7072/32000 (22%)] Loss: 0.14562 batch_time=0.20256
Train Epoch: 5 [226/1000 7232/32000 (23%)] Loss: 0.07540 batch_time=0.19759
Train Epoch: 5 [231/1000 7392/32000 (23%)] Loss: 0.03817 batch_time=0.19769
Train Epoch: 5 [236/1000 7552/32000 (24%)] Loss: 0.11313 batch_time=0.20649
Train Epoch: 5 [241/1000 7712/32000 (24%)] Loss: 0.35677 batch_time=0.20223
Train Epoch: 5 [246/1000 7872/32000 (25%)] Loss: 0.03497 batch_time=0.20165
Train Epoch: 5 [251/1000 8032/32000 (25%)] Loss: 0.10639 batch_time=0.19825
Train Epoch: 5 [256/1000 8192/32000 (26%)] Loss: 0.05814 batch_time=0.20782
Train Epoch: 5 [261/1000 8352/32000 (26%)] Loss: 0.05957 batch_time=0.19789
Train Epoch: 5 [266/1000 8512/32000 (27%)] Loss: 0.11750 batch_time=0.19917
Train Epoch: 5 [271/1000 8672/32000 (27%)] Loss: 0.07533 batch_time=0.21293
Train Epoch: 5 [276/1000 8832/32000 (28%)] Loss: 0.06820 batch_time=0.20855
Train Epoch: 5 [281/1000 8992/32000 (28%)] Loss: 0.17226 batch_time=0.19958
Train Epoch: 5 [286/1000 9152/32000 (29%)] Loss: 0.08464 batch_time=0.19878
Train Epoch: 5 [291/1000 9312/32000 (29%)] Loss: 0.04403 batch_time=0.19932
Train Epoch: 5 [296/1000 9472/32000 (30%)] Loss: 0.12404 batch_time=0.21010
Train Epoch: 5 [301/1000 9632/32000 (30%)] Loss: 0.12400 batch_time=0.19843
Train Epoch: 5 [306/1000 9792/32000 (31%)] Loss: 0.08679 batch_time=0.19772