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DCMH_MSRVTT_full.txt
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Experiment directory: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full
Preparing the dataloaders ...
Loading dataset MSRVTT_full_train in ram ...
Finish loading dataset MSRVTT_full_train in ram, taking 393.7303788661957 s.
Loading dataset MSRVTT_full_val in ram ...
Finish loading dataset MSRVTT_full_val in ram, taking 30.576141357421875 s.
Loading dataset MSRVTT_full_test in ram ...
Finish loading dataset MSRVTT_full_test in ram, taking 209.3175904750824 s.
Loading dataset MSRVTT_full_test in ram ...
Finish loading dataset MSRVTT_full_test in ram, taking 188.29560327529907 s.
Training ...
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch0.pth ...
Done in 6.838s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch0.pth ...
Done in 8.268s
epoch : 0
loss : 0
learning_rate : 5e-05
n_samples : 0
n_steps : 0
MSRVTT_full_val/t2v_metrics/R1: 0.0
MSRVTT_full_val/t2v_metrics/R5: 0.8048289738430584
MSRVTT_full_val/t2v_metrics/R10: 2.0120724346076457
MSRVTT_full_val/t2v_metrics/R50: 10.462776659959758
MSRVTT_full_val/t2v_metrics/MedR: 248.0
MSRVTT_full_val/t2v_metrics/MeanR: 247.14285714285714
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 0.0
MSRVTT_full_val/v2t_metrics/R1: 0.0
MSRVTT_full_val/v2t_metrics/R5: 0.8048289738430584
MSRVTT_full_val/v2t_metrics/R10: 1.6096579476861168
MSRVTT_full_val/v2t_metrics/R50: 10.663983903420522
MSRVTT_full_val/v2t_metrics/MedR: 252.5
MSRVTT_full_val/v2t_metrics/MeanR: 248.10965794768612
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 0.0
MSRVTT_full_test/t2v_metrics/R1: 0.033444816053511704
MSRVTT_full_test/t2v_metrics/R5: 0.16722408026755853
MSRVTT_full_test/t2v_metrics/R10: 0.36789297658862874
MSRVTT_full_test/t2v_metrics/R50: 1.6722408026755853
MSRVTT_full_test/t2v_metrics/MedR: 1497.5
MSRVTT_full_test/t2v_metrics/MeanR: 1497.7239130434782
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 0.12718904551041443
MSRVTT_full_test/v2t_metrics/R1: 0.033444816053511704
MSRVTT_full_test/v2t_metrics/R5: 0.23411371237458195
MSRVTT_full_test/v2t_metrics/R10: 0.36789297658862874
MSRVTT_full_test/v2t_metrics/R50: 1.4381270903010033
MSRVTT_full_test/v2t_metrics/MedR: 1496.75
MSRVTT_full_test/v2t_metrics/MeanR: 1498.9148829431438
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 0.14228497876638813
mnt_best : 0.12718904551041443
not_improved_count: 0
Train Epoch: 1 [1/250 128/32000 (0%)] Loss: 2.68995 (semantic_loss: 0.73938, quant_loss: 1.95020, bit_balance_loss: 0.00038) batch_time=26.08887
Train Epoch: 1 [12/250 1536/32000 (5%)] Loss: 2.00189 (semantic_loss: 0.05027, quant_loss: 1.95117, bit_balance_loss: 0.00045) batch_time=0.33792
Train Epoch: 1 [23/250 2944/32000 (9%)] Loss: 1.99655 (semantic_loss: 0.04589, quant_loss: 1.95020, bit_balance_loss: 0.00047) batch_time=0.33451
Train Epoch: 1 [34/250 4352/32000 (14%)] Loss: 1.99659 (semantic_loss: 0.04592, quant_loss: 1.95020, bit_balance_loss: 0.00048) batch_time=0.38526
Train Epoch: 1 [45/250 5760/32000 (18%)] Loss: 1.99650 (semantic_loss: 0.04582, quant_loss: 1.95020, bit_balance_loss: 0.00048) batch_time=0.36414
Train Epoch: 1 [56/250 7168/32000 (22%)] Loss: 1.99741 (semantic_loss: 0.04576, quant_loss: 1.95117, bit_balance_loss: 0.00048) batch_time=0.57415
Train Epoch: 1 [67/250 8576/32000 (27%)] Loss: 1.99642 (semantic_loss: 0.04575, quant_loss: 1.95020, bit_balance_loss: 0.00048) batch_time=0.34764
Train Epoch: 1 [78/250 9984/32000 (31%)] Loss: 1.99641 (semantic_loss: 0.04573, quant_loss: 1.95020, bit_balance_loss: 0.00048) batch_time=0.37763
Train Epoch: 1 [89/250 11392/32000 (36%)] Loss: 1.99641 (semantic_loss: 0.04574, quant_loss: 1.95020, bit_balance_loss: 0.00047) batch_time=0.34161
Train Epoch: 1 [100/250 12800/32000 (40%)] Loss: 1.99641 (semantic_loss: 0.04574, quant_loss: 1.95020, bit_balance_loss: 0.00047) batch_time=0.35712
Train Epoch: 1 [111/250 14208/32000 (44%)] Loss: 1.99738 (semantic_loss: 0.04573, quant_loss: 1.95117, bit_balance_loss: 0.00047) batch_time=0.34630
Train Epoch: 1 [122/250 15616/32000 (49%)] Loss: 1.99636 (semantic_loss: 0.04569, quant_loss: 1.95020, bit_balance_loss: 0.00047) batch_time=0.33233
Train Epoch: 1 [133/250 17024/32000 (53%)] Loss: 1.99737 (semantic_loss: 0.04573, quant_loss: 1.95117, bit_balance_loss: 0.00046) batch_time=0.38578
Train Epoch: 1 [144/250 18432/32000 (58%)] Loss: 1.99634 (semantic_loss: 0.04568, quant_loss: 1.95020, bit_balance_loss: 0.00046) batch_time=0.34605
Train Epoch: 1 [155/250 19840/32000 (62%)] Loss: 1.99731 (semantic_loss: 0.04568, quant_loss: 1.95117, bit_balance_loss: 0.00046) batch_time=0.38182
Train Epoch: 1 [166/250 21248/32000 (66%)] Loss: 1.99635 (semantic_loss: 0.04570, quant_loss: 1.95020, bit_balance_loss: 0.00045) batch_time=0.37321
Train Epoch: 1 [177/250 22656/32000 (71%)] Loss: 1.99637 (semantic_loss: 0.04572, quant_loss: 1.95020, bit_balance_loss: 0.00045) batch_time=0.41687
Train Epoch: 1 [188/250 24064/32000 (75%)] Loss: 1.99730 (semantic_loss: 0.04568, quant_loss: 1.95117, bit_balance_loss: 0.00045) batch_time=0.33890
Train Epoch: 1 [199/250 25472/32000 (80%)] Loss: 1.99729 (semantic_loss: 0.04567, quant_loss: 1.95117, bit_balance_loss: 0.00044) batch_time=0.34236
Train Epoch: 1 [210/250 26880/32000 (84%)] Loss: 1.99731 (semantic_loss: 0.04570, quant_loss: 1.95117, bit_balance_loss: 0.00044) batch_time=0.33824
Train Epoch: 1 [221/250 28288/32000 (88%)] Loss: 1.99727 (semantic_loss: 0.04567, quant_loss: 1.95117, bit_balance_loss: 0.00043) batch_time=0.33380
Train Epoch: 1 [232/250 29696/32000 (93%)] Loss: 1.99720 (semantic_loss: 0.04560, quant_loss: 1.95117, bit_balance_loss: 0.00043) batch_time=0.34787
Train Epoch: 1 [243/250 31104/32000 (97%)] Loss: 1.99724 (semantic_loss: 0.04564, quant_loss: 1.95117, bit_balance_loss: 0.00042) batch_time=0.37048
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch1.pth ...
Done in 4.320s
epoch : 1
loss : 2.002866271495819
learning_rate : 5e-05
n_samples : 32000
n_steps : 250
MSRVTT_full_val/t2v_metrics/R1: 0.2012072434607646
MSRVTT_full_val/t2v_metrics/R5: 1.2072434607645874
MSRVTT_full_val/t2v_metrics/R10: 2.0120724346076457
MSRVTT_full_val/t2v_metrics/R50: 10.865191146881287
MSRVTT_full_val/t2v_metrics/MedR: 253.0
MSRVTT_full_val/t2v_metrics/MeanR: 247.76760563380282
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 0.7876997265933326
MSRVTT_full_val/v2t_metrics/R1: 0.2012072434607646
MSRVTT_full_val/v2t_metrics/R5: 0.6036217303822937
MSRVTT_full_val/v2t_metrics/R10: 2.414486921529175
MSRVTT_full_val/v2t_metrics/R50: 10.663983903420522
MSRVTT_full_val/v2t_metrics/MedR: 249.5
MSRVTT_full_val/v2t_metrics/MeanR: 246.0472837022133
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 0.6643716798580738
MSRVTT_full_test/t2v_metrics/R1: 0.033444816053511704
MSRVTT_full_test/t2v_metrics/R5: 0.16722408026755853
MSRVTT_full_test/t2v_metrics/R10: 0.3010033444816054
MSRVTT_full_test/t2v_metrics/R50: 1.5384615384615385
MSRVTT_full_test/t2v_metrics/MedR: 1484.5
MSRVTT_full_test/t2v_metrics/MeanR: 1490.7245819397992
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 0.11895964229063753
MSRVTT_full_test/v2t_metrics/R1: 0.033444816053511704
MSRVTT_full_test/v2t_metrics/R5: 0.20066889632107024
MSRVTT_full_test/v2t_metrics/R10: 0.3010033444816054
MSRVTT_full_test/v2t_metrics/R50: 1.9063545150501673
MSRVTT_full_test/v2t_metrics/MedR: 1483.5
MSRVTT_full_test/v2t_metrics/MeanR: 1489.018227424749
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 0.1264134832670441
mnt_best : 0.12718904551041443
not_improved_count: 1
Train Epoch: 2 [1/250 128/32000 (0%)] Loss: 1.99724 (semantic_loss: 0.04565, quant_loss: 1.95117, bit_balance_loss: 0.00042) batch_time=29.64642
Train Epoch: 2 [12/250 1536/32000 (5%)] Loss: 1.99719 (semantic_loss: 0.04560, quant_loss: 1.95117, bit_balance_loss: 0.00042) batch_time=0.32946
Train Epoch: 2 [23/250 2944/32000 (9%)] Loss: 1.99620 (semantic_loss: 0.04559, quant_loss: 1.95020, bit_balance_loss: 0.00041) batch_time=0.35022
Train Epoch: 2 [34/250 4352/32000 (14%)] Loss: 1.99713 (semantic_loss: 0.04555, quant_loss: 1.95117, bit_balance_loss: 0.00041) batch_time=0.33705
Train Epoch: 2 [45/250 5760/32000 (18%)] Loss: 1.99697 (semantic_loss: 0.04539, quant_loss: 1.95117, bit_balance_loss: 0.00040) batch_time=0.39033
Train Epoch: 2 [56/250 7168/32000 (22%)] Loss: 1.99683 (semantic_loss: 0.04526, quant_loss: 1.95117, bit_balance_loss: 0.00040) batch_time=0.34449
Train Epoch: 2 [67/250 8576/32000 (27%)] Loss: 1.99695 (semantic_loss: 0.04539, quant_loss: 1.95117, bit_balance_loss: 0.00039) batch_time=0.38385
Train Epoch: 2 [78/250 9984/32000 (31%)] Loss: 1.99717 (semantic_loss: 0.04560, quant_loss: 1.95117, bit_balance_loss: 0.00040) batch_time=0.34097
Train Epoch: 2 [89/250 11392/32000 (36%)] Loss: 1.99694 (semantic_loss: 0.04538, quant_loss: 1.95117, bit_balance_loss: 0.00039) batch_time=0.33587
Train Epoch: 2 [100/250 12800/32000 (40%)] Loss: 1.99578 (semantic_loss: 0.04520, quant_loss: 1.95020, bit_balance_loss: 0.00038) batch_time=0.33670
Train Epoch: 2 [111/250 14208/32000 (44%)] Loss: 1.99636 (semantic_loss: 0.04481, quant_loss: 1.95117, bit_balance_loss: 0.00037) batch_time=0.36001
Train Epoch: 2 [122/250 15616/32000 (49%)] Loss: 1.99491 (semantic_loss: 0.04434, quant_loss: 1.95020, bit_balance_loss: 0.00037) batch_time=0.35023
Train Epoch: 2 [133/250 17024/32000 (53%)] Loss: 1.99516 (semantic_loss: 0.04459, quant_loss: 1.95020, bit_balance_loss: 0.00037) batch_time=0.36451
Train Epoch: 2 [144/250 18432/32000 (58%)] Loss: 1.99618 (semantic_loss: 0.04464, quant_loss: 1.95117, bit_balance_loss: 0.00036) batch_time=0.34205
Train Epoch: 2 [155/250 19840/32000 (62%)] Loss: 1.99425 (semantic_loss: 0.04370, quant_loss: 1.95020, bit_balance_loss: 0.00035) batch_time=0.37609
Train Epoch: 2 [166/250 21248/32000 (66%)] Loss: 1.99552 (semantic_loss: 0.04399, quant_loss: 1.95117, bit_balance_loss: 0.00035) batch_time=0.34919
Train Epoch: 2 [177/250 22656/32000 (71%)] Loss: 1.99533 (semantic_loss: 0.04381, quant_loss: 1.95117, bit_balance_loss: 0.00035) batch_time=0.33309
Train Epoch: 2 [188/250 24064/32000 (75%)] Loss: 1.99449 (semantic_loss: 0.04298, quant_loss: 1.95117, bit_balance_loss: 0.00034) batch_time=0.33277
Train Epoch: 2 [199/250 25472/32000 (80%)] Loss: 1.99416 (semantic_loss: 0.04362, quant_loss: 1.95020, bit_balance_loss: 0.00034) batch_time=0.33149
Train Epoch: 2 [210/250 26880/32000 (84%)] Loss: 1.99378 (semantic_loss: 0.04325, quant_loss: 1.95020, bit_balance_loss: 0.00034) batch_time=9.13466
Train Epoch: 2 [221/250 28288/32000 (88%)] Loss: 1.99367 (semantic_loss: 0.04314, quant_loss: 1.95020, bit_balance_loss: 0.00033) batch_time=0.33319
Train Epoch: 2 [232/250 29696/32000 (93%)] Loss: 1.99291 (semantic_loss: 0.04239, quant_loss: 1.95020, bit_balance_loss: 0.00033) batch_time=0.34405
Train Epoch: 2 [243/250 31104/32000 (97%)] Loss: 1.99284 (semantic_loss: 0.04232, quant_loss: 1.95020, bit_balance_loss: 0.00032) batch_time=0.33422
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch2.pth ...
Done in 3.901s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch2.pth ...
Done in 7.875s
removing stale ckpt [epoch 1] [took 0.00s]
removing stale ckpt [epoch 0] [took 0.00s]
epoch : 2
loss : 1.9953700456619263
learning_rate : 4.75e-05
n_samples : 64000
n_steps : 500
MSRVTT_full_val/t2v_metrics/R1: 1.0060362173038229
MSRVTT_full_val/t2v_metrics/R5: 5.4325955734406435
MSRVTT_full_val/t2v_metrics/R10: 9.054325955734406
MSRVTT_full_val/t2v_metrics/R50: 37.42454728370221
MSRVTT_full_val/t2v_metrics/MedR: 72.0
MSRVTT_full_val/t2v_metrics/MeanR: 102.24245472837022
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 3.6713492931026557
MSRVTT_full_val/v2t_metrics/R1: 0.2012072434607646
MSRVTT_full_val/v2t_metrics/R5: 4.0241448692152915
MSRVTT_full_val/v2t_metrics/R10: 7.645875251509055
MSRVTT_full_val/v2t_metrics/R50: 37.42454728370221
MSRVTT_full_val/v2t_metrics/MedR: 69.5
MSRVTT_full_val/v2t_metrics/MeanR: 94.33802816901408
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 1.8361781228921394
MSRVTT_full_test/t2v_metrics/R1: 0.13377926421404682
MSRVTT_full_test/t2v_metrics/R5: 0.9364548494983278
MSRVTT_full_test/t2v_metrics/R10: 1.605351170568562
MSRVTT_full_test/t2v_metrics/R50: 8.494983277591974
MSRVTT_full_test/t2v_metrics/MedR: 449.75
MSRVTT_full_test/t2v_metrics/MeanR: 632.0481605351171
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 0.585888848145537
MSRVTT_full_test/v2t_metrics/R1: 0.16722408026755853
MSRVTT_full_test/v2t_metrics/R5: 0.9698996655518395
MSRVTT_full_test/v2t_metrics/R10: 1.5050167224080269
MSRVTT_full_test/v2t_metrics/R50: 6.8561872909699
MSRVTT_full_test/v2t_metrics/MedR: 428.75
MSRVTT_full_test/v2t_metrics/MeanR: 585.9797658862876
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 0.6249649340541872
mnt_best : 0.585888848145537
not_improved_count: 0
Train Epoch: 3 [1/250 128/32000 (0%)] Loss: 1.99200 (semantic_loss: 0.04149, quant_loss: 1.95020, bit_balance_loss: 0.00032) batch_time=30.28709
Train Epoch: 3 [12/250 1536/32000 (5%)] Loss: 1.99178 (semantic_loss: 0.04127, quant_loss: 1.95020, bit_balance_loss: 0.00031) batch_time=0.34835
Train Epoch: 3 [23/250 2944/32000 (9%)] Loss: 1.99193 (semantic_loss: 0.04143, quant_loss: 1.95020, bit_balance_loss: 0.00031) batch_time=0.33878
Train Epoch: 3 [34/250 4352/32000 (14%)] Loss: 1.99165 (semantic_loss: 0.04115, quant_loss: 1.95020, bit_balance_loss: 0.00031) batch_time=0.35745
Train Epoch: 3 [45/250 5760/32000 (18%)] Loss: 1.99085 (semantic_loss: 0.04036, quant_loss: 1.95020, bit_balance_loss: 0.00030) batch_time=0.33453
Train Epoch: 3 [56/250 7168/32000 (22%)] Loss: 1.98904 (semantic_loss: 0.03953, quant_loss: 1.94922, bit_balance_loss: 0.00030) batch_time=0.34739
Train Epoch: 3 [67/250 8576/32000 (27%)] Loss: 1.98974 (semantic_loss: 0.03925, quant_loss: 1.95020, bit_balance_loss: 0.00029) batch_time=0.34280
Train Epoch: 3 [78/250 9984/32000 (31%)] Loss: 1.98893 (semantic_loss: 0.03845, quant_loss: 1.95020, bit_balance_loss: 0.00029) batch_time=0.37447
Train Epoch: 3 [89/250 11392/32000 (36%)] Loss: 1.98923 (semantic_loss: 0.03874, quant_loss: 1.95020, bit_balance_loss: 0.00029) batch_time=0.34134
Train Epoch: 3 [100/250 12800/32000 (40%)] Loss: 1.98837 (semantic_loss: 0.03887, quant_loss: 1.94922, bit_balance_loss: 0.00028) batch_time=0.35172
Train Epoch: 3 [111/250 14208/32000 (44%)] Loss: 1.98893 (semantic_loss: 0.03845, quant_loss: 1.95020, bit_balance_loss: 0.00028) batch_time=0.35852
Train Epoch: 3 [122/250 15616/32000 (49%)] Loss: 1.98808 (semantic_loss: 0.03761, quant_loss: 1.95020, bit_balance_loss: 0.00028) batch_time=0.34807
Train Epoch: 3 [133/250 17024/32000 (53%)] Loss: 1.98791 (semantic_loss: 0.03744, quant_loss: 1.95020, bit_balance_loss: 0.00027) batch_time=0.33686
Train Epoch: 3 [144/250 18432/32000 (58%)] Loss: 1.98632 (semantic_loss: 0.03585, quant_loss: 1.95020, bit_balance_loss: 0.00027) batch_time=0.35561
Train Epoch: 3 [155/250 19840/32000 (62%)] Loss: 1.98634 (semantic_loss: 0.03685, quant_loss: 1.94922, bit_balance_loss: 0.00027) batch_time=0.32573
Train Epoch: 3 [166/250 21248/32000 (66%)] Loss: 1.98539 (semantic_loss: 0.03590, quant_loss: 1.94922, bit_balance_loss: 0.00027) batch_time=0.34143
Train Epoch: 3 [177/250 22656/32000 (71%)] Loss: 1.98685 (semantic_loss: 0.03640, quant_loss: 1.95020, bit_balance_loss: 0.00026) batch_time=0.36701
Train Epoch: 3 [188/250 24064/32000 (75%)] Loss: 1.98597 (semantic_loss: 0.03551, quant_loss: 1.95020, bit_balance_loss: 0.00026) batch_time=0.33286
Train Epoch: 3 [199/250 25472/32000 (80%)] Loss: 1.98598 (semantic_loss: 0.03650, quant_loss: 1.94922, bit_balance_loss: 0.00026) batch_time=0.36483
Train Epoch: 3 [210/250 26880/32000 (84%)] Loss: 1.98507 (semantic_loss: 0.03559, quant_loss: 1.94922, bit_balance_loss: 0.00026) batch_time=2.70443
Train Epoch: 3 [221/250 28288/32000 (88%)] Loss: 1.98550 (semantic_loss: 0.03505, quant_loss: 1.95020, bit_balance_loss: 0.00025) batch_time=0.35194
Train Epoch: 3 [232/250 29696/32000 (93%)] Loss: 1.98538 (semantic_loss: 0.03493, quant_loss: 1.95020, bit_balance_loss: 0.00025) batch_time=0.39445
Train Epoch: 3 [243/250 31104/32000 (97%)] Loss: 1.98415 (semantic_loss: 0.03371, quant_loss: 1.95020, bit_balance_loss: 0.00025) batch_time=0.34545
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch3.pth ...
Done in 18.073s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch3.pth ...
Done in 22.142s
removing stale ckpt [epoch 2] [took 0.00s]
epoch : 3
loss : 1.9879206166267396
learning_rate : 4.5125e-05
n_samples : 96000
n_steps : 750
MSRVTT_full_val/t2v_metrics/R1: 4.627766599597585
MSRVTT_full_val/t2v_metrics/R5: 19.718309859154928
MSRVTT_full_val/t2v_metrics/R10: 32.99798792756539
MSRVTT_full_val/t2v_metrics/R50: 79.87927565392354
MSRVTT_full_val/t2v_metrics/MedR: 18.5
MSRVTT_full_val/t2v_metrics/MeanR: 34.783702213279675
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 14.440299400640399
MSRVTT_full_val/v2t_metrics/R1: 3.8229376257545273
MSRVTT_full_val/v2t_metrics/R5: 18.309859154929576
MSRVTT_full_val/v2t_metrics/R10: 33.40040241448692
MSRVTT_full_val/v2t_metrics/R50: 80.28169014084507
MSRVTT_full_val/v2t_metrics/MedR: 20.5
MSRVTT_full_val/v2t_metrics/MeanR: 32.87122736418511
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 13.272252590903882
MSRVTT_full_test/t2v_metrics/R1: 0.7023411371237458
MSRVTT_full_test/t2v_metrics/R5: 3.4448160535117056
MSRVTT_full_test/t2v_metrics/R10: 7.25752508361204
MSRVTT_full_test/t2v_metrics/R50: 28.729096989966557
MSRVTT_full_test/t2v_metrics/MedR: 117.5
MSRVTT_full_test/t2v_metrics/MeanR: 216.80969899665553
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 2.5991672695074564
MSRVTT_full_test/v2t_metrics/R1: 0.6354515050167224
MSRVTT_full_test/v2t_metrics/R5: 3.7123745819397995
MSRVTT_full_test/v2t_metrics/R10: 6.989966555183947
MSRVTT_full_test/v2t_metrics/R50: 29.23076923076923
MSRVTT_full_test/v2t_metrics/MedR: 107.5
MSRVTT_full_test/v2t_metrics/MeanR: 206.86254180602006
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 2.545285090957286
mnt_best : 2.5991672695074564
not_improved_count: 0
Train Epoch: 4 [1/250 128/32000 (0%)] Loss: 1.98320 (semantic_loss: 0.03373, quant_loss: 1.94922, bit_balance_loss: 0.00025) batch_time=30.88091
Train Epoch: 4 [12/250 1536/32000 (5%)] Loss: 1.98299 (semantic_loss: 0.03353, quant_loss: 1.94922, bit_balance_loss: 0.00025) batch_time=0.35681
Train Epoch: 4 [23/250 2944/32000 (9%)] Loss: 1.98373 (semantic_loss: 0.03427, quant_loss: 1.94922, bit_balance_loss: 0.00024) batch_time=0.35605
Train Epoch: 4 [34/250 4352/32000 (14%)] Loss: 1.98373 (semantic_loss: 0.03427, quant_loss: 1.94922, bit_balance_loss: 0.00024) batch_time=0.34194
Train Epoch: 4 [45/250 5760/32000 (18%)] Loss: 1.98312 (semantic_loss: 0.03366, quant_loss: 1.94922, bit_balance_loss: 0.00024) batch_time=0.36047
Train Epoch: 4 [56/250 7168/32000 (22%)] Loss: 1.98378 (semantic_loss: 0.03335, quant_loss: 1.95020, bit_balance_loss: 0.00023) batch_time=0.36644
Train Epoch: 4 [67/250 8576/32000 (27%)] Loss: 1.98406 (semantic_loss: 0.03461, quant_loss: 1.94922, bit_balance_loss: 0.00023) batch_time=1.80795
Train Epoch: 4 [78/250 9984/32000 (31%)] Loss: 1.98124 (semantic_loss: 0.03179, quant_loss: 1.94922, bit_balance_loss: 0.00023) batch_time=0.34707
Train Epoch: 4 [89/250 11392/32000 (36%)] Loss: 1.98078 (semantic_loss: 0.03133, quant_loss: 1.94922, bit_balance_loss: 0.00023) batch_time=0.34196
Train Epoch: 4 [100/250 12800/32000 (40%)] Loss: 1.98209 (semantic_loss: 0.03264, quant_loss: 1.94922, bit_balance_loss: 0.00022) batch_time=0.36813
Train Epoch: 4 [111/250 14208/32000 (44%)] Loss: 1.98153 (semantic_loss: 0.03209, quant_loss: 1.94922, bit_balance_loss: 0.00022) batch_time=0.38684
Train Epoch: 4 [122/250 15616/32000 (49%)] Loss: 1.98300 (semantic_loss: 0.03259, quant_loss: 1.95020, bit_balance_loss: 0.00022) batch_time=0.43110
Train Epoch: 4 [133/250 17024/32000 (53%)] Loss: 1.98204 (semantic_loss: 0.03163, quant_loss: 1.95020, bit_balance_loss: 0.00022) batch_time=0.58454
Train Epoch: 4 [144/250 18432/32000 (58%)] Loss: 1.98173 (semantic_loss: 0.03229, quant_loss: 1.94922, bit_balance_loss: 0.00022) batch_time=0.34559
Train Epoch: 4 [155/250 19840/32000 (62%)] Loss: 1.98109 (semantic_loss: 0.03165, quant_loss: 1.94922, bit_balance_loss: 0.00022) batch_time=0.35049
Train Epoch: 4 [166/250 21248/32000 (66%)] Loss: 1.97992 (semantic_loss: 0.03048, quant_loss: 1.94922, bit_balance_loss: 0.00022) batch_time=0.35154
Train Epoch: 4 [177/250 22656/32000 (71%)] Loss: 1.98079 (semantic_loss: 0.03136, quant_loss: 1.94922, bit_balance_loss: 0.00021) batch_time=0.36151
Train Epoch: 4 [188/250 24064/32000 (75%)] Loss: 1.98055 (semantic_loss: 0.03112, quant_loss: 1.94922, bit_balance_loss: 0.00021) batch_time=0.36025
Train Epoch: 4 [199/250 25472/32000 (80%)] Loss: 1.97908 (semantic_loss: 0.02966, quant_loss: 1.94922, bit_balance_loss: 0.00021) batch_time=11.41206
Train Epoch: 4 [210/250 26880/32000 (84%)] Loss: 1.97929 (semantic_loss: 0.02986, quant_loss: 1.94922, bit_balance_loss: 0.00020) batch_time=0.34213
Train Epoch: 4 [221/250 28288/32000 (88%)] Loss: 1.97957 (semantic_loss: 0.03015, quant_loss: 1.94922, bit_balance_loss: 0.00020) batch_time=0.33568
Train Epoch: 4 [232/250 29696/32000 (93%)] Loss: 1.98094 (semantic_loss: 0.03152, quant_loss: 1.94922, bit_balance_loss: 0.00020) batch_time=0.36028
Train Epoch: 4 [243/250 31104/32000 (97%)] Loss: 1.97967 (semantic_loss: 0.03025, quant_loss: 1.94922, bit_balance_loss: 0.00020) batch_time=0.36185
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch4.pth ...
Done in 3.964s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch4.pth ...
Done in 7.993s
removing stale ckpt [epoch 3] [took 0.00s]
epoch : 4
loss : 1.981800720691681
learning_rate : 4.2868749999999995e-05
n_samples : 128000
n_steps : 1000
MSRVTT_full_val/t2v_metrics/R1: 7.847082494969819
MSRVTT_full_val/t2v_metrics/R5: 31.790744466800806
MSRVTT_full_val/t2v_metrics/R10: 47.88732394366197
MSRVTT_full_val/t2v_metrics/R50: 89.738430583501
MSRVTT_full_val/t2v_metrics/MedR: 11.0
MSRVTT_full_val/t2v_metrics/MeanR: 23.00301810865191
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 22.860014153411303
MSRVTT_full_val/v2t_metrics/R1: 8.249496981891348
MSRVTT_full_val/v2t_metrics/R5: 32.19315895372233
MSRVTT_full_val/v2t_metrics/R10: 51.30784708249497
MSRVTT_full_val/v2t_metrics/R50: 89.33601609657947
MSRVTT_full_val/v2t_metrics/MedR: 10.0
MSRVTT_full_val/v2t_metrics/MeanR: 22.096579476861166
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 23.884983807927465
MSRVTT_full_test/t2v_metrics/R1: 1.939799331103679
MSRVTT_full_test/t2v_metrics/R5: 8.528428093645484
MSRVTT_full_test/t2v_metrics/R10: 14.749163879598662
MSRVTT_full_test/t2v_metrics/R50: 46.187290969899664
MSRVTT_full_test/t2v_metrics/MedR: 59.5
MSRVTT_full_test/t2v_metrics/MeanR: 131.4670568561873
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 6.248815942833558
MSRVTT_full_test/v2t_metrics/R1: 1.6387959866220736
MSRVTT_full_test/v2t_metrics/R5: 8.294314381270903
MSRVTT_full_test/v2t_metrics/R10: 15.384615384615385
MSRVTT_full_test/v2t_metrics/R50: 46.42140468227425
MSRVTT_full_test/v2t_metrics/MedR: 59.5
MSRVTT_full_test/v2t_metrics/MeanR: 126.68645484949833
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 5.935591567733011
mnt_best : 6.248815942833558
not_improved_count: 0
Train Epoch: 5 [1/250 128/32000 (0%)] Loss: 1.97853 (semantic_loss: 0.02911, quant_loss: 1.94922, bit_balance_loss: 0.00020) batch_time=31.82514
Train Epoch: 5 [12/250 1536/32000 (5%)] Loss: 1.98001 (semantic_loss: 0.02962, quant_loss: 1.95020, bit_balance_loss: 0.00019) batch_time=0.35429
Train Epoch: 5 [23/250 2944/32000 (9%)] Loss: 1.97944 (semantic_loss: 0.02905, quant_loss: 1.95020, bit_balance_loss: 0.00019) batch_time=0.35861
Train Epoch: 5 [34/250 4352/32000 (14%)] Loss: 1.97944 (semantic_loss: 0.02905, quant_loss: 1.95020, bit_balance_loss: 0.00019) batch_time=0.36076
Train Epoch: 5 [45/250 5760/32000 (18%)] Loss: 1.97968 (semantic_loss: 0.02929, quant_loss: 1.95020, bit_balance_loss: 0.00019) batch_time=0.33256
Train Epoch: 5 [56/250 7168/32000 (22%)] Loss: 1.97907 (semantic_loss: 0.02869, quant_loss: 1.95020, bit_balance_loss: 0.00019) batch_time=0.34480
Train Epoch: 5 [67/250 8576/32000 (27%)] Loss: 1.97925 (semantic_loss: 0.02985, quant_loss: 1.94922, bit_balance_loss: 0.00019) batch_time=0.34551
Train Epoch: 5 [78/250 9984/32000 (31%)] Loss: 1.97671 (semantic_loss: 0.02731, quant_loss: 1.94922, bit_balance_loss: 0.00018) batch_time=2.03563
Train Epoch: 5 [89/250 11392/32000 (36%)] Loss: 1.97932 (semantic_loss: 0.02894, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.41573
Train Epoch: 5 [100/250 12800/32000 (40%)] Loss: 1.97995 (semantic_loss: 0.02957, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.36758
Train Epoch: 5 [111/250 14208/32000 (44%)] Loss: 1.97977 (semantic_loss: 0.02939, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.33191
Train Epoch: 5 [122/250 15616/32000 (49%)] Loss: 1.97934 (semantic_loss: 0.02896, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.34735
Train Epoch: 5 [133/250 17024/32000 (53%)] Loss: 1.98062 (semantic_loss: 0.03024, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.33431
Train Epoch: 5 [144/250 18432/32000 (58%)] Loss: 1.97802 (semantic_loss: 0.02764, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=3.69417
Train Epoch: 5 [155/250 19840/32000 (62%)] Loss: 1.97851 (semantic_loss: 0.02813, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.34629
Train Epoch: 5 [166/250 21248/32000 (66%)] Loss: 1.97867 (semantic_loss: 0.02830, quant_loss: 1.95020, bit_balance_loss: 0.00017) batch_time=0.39615
Train Epoch: 5 [177/250 22656/32000 (71%)] Loss: 1.97715 (semantic_loss: 0.02775, quant_loss: 1.94922, bit_balance_loss: 0.00018) batch_time=0.40368
Train Epoch: 5 [188/250 24064/32000 (75%)] Loss: 1.97826 (semantic_loss: 0.02788, quant_loss: 1.95020, bit_balance_loss: 0.00018) batch_time=0.36848
Train Epoch: 5 [199/250 25472/32000 (80%)] Loss: 1.97751 (semantic_loss: 0.02714, quant_loss: 1.95020, bit_balance_loss: 0.00017) batch_time=0.38557
Train Epoch: 5 [210/250 26880/32000 (84%)] Loss: 1.97690 (semantic_loss: 0.02751, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.33105
Train Epoch: 5 [221/250 28288/32000 (88%)] Loss: 1.97816 (semantic_loss: 0.02779, quant_loss: 1.95020, bit_balance_loss: 0.00017) batch_time=0.33467
Train Epoch: 5 [232/250 29696/32000 (93%)] Loss: 1.97807 (semantic_loss: 0.02868, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.35748
Train Epoch: 5 [243/250 31104/32000 (97%)] Loss: 1.97668 (semantic_loss: 0.02729, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.34886
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch5.pth ...
Done in 4.512s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch5.pth ...
Done in 8.919s
removing stale ckpt [epoch 4] [took 0.00s]
epoch : 5
loss : 1.9788992266654968
learning_rate : 4.072531249999999e-05
n_samples : 160000
n_steps : 1250
MSRVTT_full_val/t2v_metrics/R1: 10.663983903420522
MSRVTT_full_val/t2v_metrics/R5: 37.625754527162975
MSRVTT_full_val/t2v_metrics/R10: 56.94164989939638
MSRVTT_full_val/t2v_metrics/R50: 90.3420523138833
MSRVTT_full_val/t2v_metrics/MedR: 9.0
MSRVTT_full_val/t2v_metrics/MeanR: 19.180080482897385
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 28.37559096584382
MSRVTT_full_val/v2t_metrics/R1: 11.267605633802816
MSRVTT_full_val/v2t_metrics/R5: 34.80885311871227
MSRVTT_full_val/v2t_metrics/R10: 55.734406438631794
MSRVTT_full_val/v2t_metrics/R50: 91.75050301810865
MSRVTT_full_val/v2t_metrics/MedR: 9.0
MSRVTT_full_val/v2t_metrics/MeanR: 19.10764587525151
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 27.960713166154818
MSRVTT_full_test/t2v_metrics/R1: 2.508361204013378
MSRVTT_full_test/t2v_metrics/R5: 11.471571906354516
MSRVTT_full_test/t2v_metrics/R10: 19.598662207357858
MSRVTT_full_test/t2v_metrics/R50: 54.11371237458194
MSRVTT_full_test/t2v_metrics/MedR: 43.0
MSRVTT_full_test/t2v_metrics/MeanR: 104.01003344481606
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 8.261897667957863
MSRVTT_full_test/v2t_metrics/R1: 2.6421404682274248
MSRVTT_full_test/v2t_metrics/R5: 11.103678929765886
MSRVTT_full_test/v2t_metrics/R10: 19.36454849498328
MSRVTT_full_test/v2t_metrics/R50: 55.919732441471574
MSRVTT_full_test/v2t_metrics/MedR: 40.5
MSRVTT_full_test/v2t_metrics/MeanR: 103.30200668896322
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 8.282155709679547
mnt_best : 8.261897667957863
not_improved_count: 0
Train Epoch: 6 [1/250 128/32000 (0%)] Loss: 1.97648 (semantic_loss: 0.02612, quant_loss: 1.95020, bit_balance_loss: 0.00017) batch_time=29.45428
Train Epoch: 6 [12/250 1536/32000 (5%)] Loss: 1.97656 (semantic_loss: 0.02620, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.35568
Train Epoch: 6 [23/250 2944/32000 (9%)] Loss: 1.97700 (semantic_loss: 0.02761, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.34420
Train Epoch: 6 [34/250 4352/32000 (14%)] Loss: 1.97773 (semantic_loss: 0.02834, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.34012
Train Epoch: 6 [45/250 5760/32000 (18%)] Loss: 1.97644 (semantic_loss: 0.02705, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.36547
Train Epoch: 6 [56/250 7168/32000 (22%)] Loss: 1.97789 (semantic_loss: 0.02851, quant_loss: 1.94922, bit_balance_loss: 0.00016) batch_time=0.33875
Train Epoch: 6 [67/250 8576/32000 (27%)] Loss: 1.97893 (semantic_loss: 0.02856, quant_loss: 1.95020, bit_balance_loss: 0.00017) batch_time=0.34837
Train Epoch: 6 [78/250 9984/32000 (31%)] Loss: 1.97774 (semantic_loss: 0.02836, quant_loss: 1.94922, bit_balance_loss: 0.00016) batch_time=0.35085
Train Epoch: 6 [89/250 11392/32000 (36%)] Loss: 1.97811 (semantic_loss: 0.02872, quant_loss: 1.94922, bit_balance_loss: 0.00017) batch_time=0.33158
Train Epoch: 6 [100/250 12800/32000 (40%)] Loss: 1.97794 (semantic_loss: 0.02758, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.38993
Train Epoch: 6 [111/250 14208/32000 (44%)] Loss: 1.97794 (semantic_loss: 0.02759, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.34195
Train Epoch: 6 [122/250 15616/32000 (49%)] Loss: 1.97740 (semantic_loss: 0.02704, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.35524
Train Epoch: 6 [133/250 17024/32000 (53%)] Loss: 1.97673 (semantic_loss: 0.02638, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.34024
Train Epoch: 6 [144/250 18432/32000 (58%)] Loss: 1.97866 (semantic_loss: 0.02830, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.36063
Train Epoch: 6 [155/250 19840/32000 (62%)] Loss: 1.97687 (semantic_loss: 0.02749, quant_loss: 1.94922, bit_balance_loss: 0.00016) batch_time=0.33578
Train Epoch: 6 [166/250 21248/32000 (66%)] Loss: 1.97788 (semantic_loss: 0.02753, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.34097
Train Epoch: 6 [177/250 22656/32000 (71%)] Loss: 1.97718 (semantic_loss: 0.02683, quant_loss: 1.95020, bit_balance_loss: 0.00016) batch_time=0.34022
Train Epoch: 6 [188/250 24064/32000 (75%)] Loss: 1.97478 (semantic_loss: 0.02443, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.37531
Train Epoch: 6 [199/250 25472/32000 (80%)] Loss: 1.97517 (semantic_loss: 0.02580, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.38872
Train Epoch: 6 [210/250 26880/32000 (84%)] Loss: 1.97631 (semantic_loss: 0.02694, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.33514
Train Epoch: 6 [221/250 28288/32000 (88%)] Loss: 1.97674 (semantic_loss: 0.02737, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=1.07921
Train Epoch: 6 [232/250 29696/32000 (93%)] Loss: 1.97440 (semantic_loss: 0.02503, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.46266
Train Epoch: 6 [243/250 31104/32000 (97%)] Loss: 1.97891 (semantic_loss: 0.02857, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.33183
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch6.pth ...
Done in 4.294s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch6.pth ...
Done in 8.285s
removing stale ckpt [epoch 5] [took 0.00s]
epoch : 6
loss : 1.9769243006706239
learning_rate : 3.868904687499999e-05
n_samples : 192000
n_steps : 1500
MSRVTT_full_val/t2v_metrics/R1: 12.273641851106639
MSRVTT_full_val/t2v_metrics/R5: 42.454728370221325
MSRVTT_full_val/t2v_metrics/R10: 59.55734406438632
MSRVTT_full_val/t2v_metrics/R50: 91.54929577464789
MSRVTT_full_val/t2v_metrics/MedR: 8.0
MSRVTT_full_val/t2v_metrics/MeanR: 18.046277665995976
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 31.425216500338678
MSRVTT_full_val/v2t_metrics/R1: 12.072434607645874
MSRVTT_full_val/v2t_metrics/R5: 46.07645875251509
MSRVTT_full_val/v2t_metrics/R10: 62.374245472837025
MSRVTT_full_val/v2t_metrics/R50: 92.5553319919517
MSRVTT_full_val/v2t_metrics/MedR: 6.0
MSRVTT_full_val/v2t_metrics/MeanR: 16.78672032193159
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 32.6156786946158
MSRVTT_full_test/t2v_metrics/R1: 4.247491638795987
MSRVTT_full_test/t2v_metrics/R5: 15.217391304347826
MSRVTT_full_test/t2v_metrics/R10: 25.85284280936455
MSRVTT_full_test/t2v_metrics/R50: 60.869565217391305
MSRVTT_full_test/t2v_metrics/MedR: 32.0
MSRVTT_full_test/t2v_metrics/MeanR: 88.52959866220736
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 11.866619458144127
MSRVTT_full_test/v2t_metrics/R1: 3.678929765886288
MSRVTT_full_test/v2t_metrics/R5: 15.852842809364548
MSRVTT_full_test/v2t_metrics/R10: 25.953177257525084
MSRVTT_full_test/v2t_metrics/R50: 62.508361204013376
MSRVTT_full_test/v2t_metrics/MedR: 30.5
MSRVTT_full_test/v2t_metrics/MeanR: 84.85752508361205
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 11.48170526560581
mnt_best : 11.866619458144127
not_improved_count: 0
Train Epoch: 7 [1/250 128/32000 (0%)] Loss: 1.97444 (semantic_loss: 0.02507, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=28.10122
Train Epoch: 7 [12/250 1536/32000 (5%)] Loss: 1.97502 (semantic_loss: 0.02467, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.36254
Train Epoch: 7 [23/250 2944/32000 (9%)] Loss: 1.97558 (semantic_loss: 0.02621, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.34553
Train Epoch: 7 [34/250 4352/32000 (14%)] Loss: 1.97528 (semantic_loss: 0.02493, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34276
Train Epoch: 7 [45/250 5760/32000 (18%)] Loss: 1.97659 (semantic_loss: 0.02624, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34612
Train Epoch: 7 [56/250 7168/32000 (22%)] Loss: 1.97507 (semantic_loss: 0.02472, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.36783
Train Epoch: 7 [67/250 8576/32000 (27%)] Loss: 1.97549 (semantic_loss: 0.02612, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.45175
Train Epoch: 7 [78/250 9984/32000 (31%)] Loss: 1.97513 (semantic_loss: 0.02576, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=3.77321
Train Epoch: 7 [89/250 11392/32000 (36%)] Loss: 1.97397 (semantic_loss: 0.02461, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.37438
Train Epoch: 7 [100/250 12800/32000 (40%)] Loss: 1.97724 (semantic_loss: 0.02690, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.36891
Train Epoch: 7 [111/250 14208/32000 (44%)] Loss: 1.97495 (semantic_loss: 0.02461, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.33957
Train Epoch: 7 [122/250 15616/32000 (49%)] Loss: 1.97612 (semantic_loss: 0.02577, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34689
Train Epoch: 7 [133/250 17024/32000 (53%)] Loss: 1.97371 (semantic_loss: 0.02434, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.47549
Train Epoch: 7 [144/250 18432/32000 (58%)] Loss: 1.97519 (semantic_loss: 0.02582, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=3.31274
Train Epoch: 7 [155/250 19840/32000 (62%)] Loss: 1.97343 (semantic_loss: 0.02406, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.38191
Train Epoch: 7 [166/250 21248/32000 (66%)] Loss: 1.97391 (semantic_loss: 0.02455, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.32741
Train Epoch: 7 [177/250 22656/32000 (71%)] Loss: 1.97699 (semantic_loss: 0.02664, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34110
Train Epoch: 7 [188/250 24064/32000 (75%)] Loss: 1.97384 (semantic_loss: 0.02448, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.45855
Train Epoch: 7 [199/250 25472/32000 (80%)] Loss: 1.97457 (semantic_loss: 0.02423, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.35592
Train Epoch: 7 [210/250 26880/32000 (84%)] Loss: 1.97518 (semantic_loss: 0.02484, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=1.36500
Train Epoch: 7 [221/250 28288/32000 (88%)] Loss: 1.97523 (semantic_loss: 0.02489, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34089
Train Epoch: 7 [232/250 29696/32000 (93%)] Loss: 1.97430 (semantic_loss: 0.02493, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.33147
Train Epoch: 7 [243/250 31104/32000 (97%)] Loss: 1.97597 (semantic_loss: 0.02660, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.34283
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch7.pth ...
Done in 4.032s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch7.pth ...
Done in 8.043s
removing stale ckpt [epoch 6] [took 0.01s]
epoch : 7
loss : 1.9751533880233765
learning_rate : 3.675459453124999e-05
n_samples : 224000
n_steps : 1750
MSRVTT_full_val/t2v_metrics/R1: 14.084507042253522
MSRVTT_full_val/t2v_metrics/R5: 49.899396378269614
MSRVTT_full_val/t2v_metrics/R10: 67.20321931589537
MSRVTT_full_val/t2v_metrics/R50: 92.35412474849095
MSRVTT_full_val/t2v_metrics/MedR: 6.0
MSRVTT_full_val/t2v_metrics/MeanR: 15.927565392354126
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 36.14728421338337
MSRVTT_full_val/v2t_metrics/R1: 15.090543259557345
MSRVTT_full_val/v2t_metrics/R5: 51.10663983903421
MSRVTT_full_val/v2t_metrics/R10: 69.01408450704226
MSRVTT_full_val/v2t_metrics/R50: 93.158953722334
MSRVTT_full_val/v2t_metrics/MedR: 5.5
MSRVTT_full_val/v2t_metrics/MeanR: 14.87625754527163
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 37.61606058691163
MSRVTT_full_test/t2v_metrics/R1: 4.414715719063545
MSRVTT_full_test/t2v_metrics/R5: 16.354515050167223
MSRVTT_full_test/t2v_metrics/R10: 26.989966555183948
MSRVTT_full_test/t2v_metrics/R50: 64.18060200668896
MSRVTT_full_test/t2v_metrics/MedR: 28.0
MSRVTT_full_test/t2v_metrics/MeanR: 80.58277591973244
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 12.490531530457323
MSRVTT_full_test/v2t_metrics/R1: 4.381270903010034
MSRVTT_full_test/v2t_metrics/R5: 18.294314381270905
MSRVTT_full_test/v2t_metrics/R10: 28.963210702341136
MSRVTT_full_test/v2t_metrics/R50: 65.41806020066889
MSRVTT_full_test/v2t_metrics/MedR: 27.0
MSRVTT_full_test/v2t_metrics/MeanR: 76.74280936454849
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 13.241006019901905
mnt_best : 12.490531530457323
not_improved_count: 0
Train Epoch: 8 [1/250 128/32000 (0%)] Loss: 1.97396 (semantic_loss: 0.02460, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=34.75777
Train Epoch: 8 [12/250 1536/32000 (5%)] Loss: 1.97592 (semantic_loss: 0.02655, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.35870
Train Epoch: 8 [23/250 2944/32000 (9%)] Loss: 1.97432 (semantic_loss: 0.02398, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34477
Train Epoch: 8 [34/250 4352/32000 (14%)] Loss: 1.97494 (semantic_loss: 0.02558, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33931
Train Epoch: 8 [45/250 5760/32000 (18%)] Loss: 1.97302 (semantic_loss: 0.02366, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.35312
Train Epoch: 8 [56/250 7168/32000 (22%)] Loss: 1.97482 (semantic_loss: 0.02448, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37888
Train Epoch: 8 [67/250 8576/32000 (27%)] Loss: 1.97355 (semantic_loss: 0.02419, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.36390
Train Epoch: 8 [78/250 9984/32000 (31%)] Loss: 1.97585 (semantic_loss: 0.02649, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.37229
Train Epoch: 8 [89/250 11392/32000 (36%)] Loss: 1.97508 (semantic_loss: 0.02474, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33683
Train Epoch: 8 [100/250 12800/32000 (40%)] Loss: 1.97491 (semantic_loss: 0.02457, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35116
Train Epoch: 8 [111/250 14208/32000 (44%)] Loss: 1.97570 (semantic_loss: 0.02536, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33270
Train Epoch: 8 [122/250 15616/32000 (49%)] Loss: 1.97251 (semantic_loss: 0.02217, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.36716
Train Epoch: 8 [133/250 17024/32000 (53%)] Loss: 1.97336 (semantic_loss: 0.02399, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.36934
Train Epoch: 8 [144/250 18432/32000 (58%)] Loss: 1.97387 (semantic_loss: 0.02353, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37638
Train Epoch: 8 [155/250 19840/32000 (62%)] Loss: 1.97591 (semantic_loss: 0.02556, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34041
Train Epoch: 8 [166/250 21248/32000 (66%)] Loss: 1.97295 (semantic_loss: 0.02358, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34557
Train Epoch: 8 [177/250 22656/32000 (71%)] Loss: 1.97451 (semantic_loss: 0.02514, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34627
Train Epoch: 8 [188/250 24064/32000 (75%)] Loss: 1.97211 (semantic_loss: 0.02274, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.37927
Train Epoch: 8 [199/250 25472/32000 (80%)] Loss: 1.97212 (semantic_loss: 0.02275, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.37334
Train Epoch: 8 [210/250 26880/32000 (84%)] Loss: 1.97631 (semantic_loss: 0.02597, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=4.56336
Train Epoch: 8 [221/250 28288/32000 (88%)] Loss: 1.97428 (semantic_loss: 0.02394, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37028
Train Epoch: 8 [232/250 29696/32000 (93%)] Loss: 1.97361 (semantic_loss: 0.02327, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34190
Train Epoch: 8 [243/250 31104/32000 (97%)] Loss: 1.97339 (semantic_loss: 0.02304, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.33536
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch8.pth ...
Done in 4.039s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch8.pth ...
Done in 7.759s
removing stale ckpt [epoch 7] [took 0.00s]
epoch : 8
loss : 1.9740591506958007
learning_rate : 3.4916864804687486e-05
n_samples : 256000
n_steps : 2000
MSRVTT_full_val/t2v_metrics/R1: 17.303822937625753
MSRVTT_full_val/t2v_metrics/R5: 51.10663983903421
MSRVTT_full_val/t2v_metrics/R10: 68.41046277665995
MSRVTT_full_val/t2v_metrics/R50: 92.75653923541248
MSRVTT_full_val/t2v_metrics/MedR: 5.0
MSRVTT_full_val/t2v_metrics/MeanR: 15.16297786720322
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 39.25671661427181
MSRVTT_full_val/v2t_metrics/R1: 16.29778672032193
MSRVTT_full_val/v2t_metrics/R5: 54.12474849094568
MSRVTT_full_val/v2t_metrics/R10: 71.62977867203219
MSRVTT_full_val/v2t_metrics/R50: 92.5553319919517
MSRVTT_full_val/v2t_metrics/MedR: 5.0
MSRVTT_full_val/v2t_metrics/MeanR: 13.88128772635815
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 39.82960904683676
MSRVTT_full_test/t2v_metrics/R1: 4.448160535117057
MSRVTT_full_test/t2v_metrics/R5: 18.99665551839465
MSRVTT_full_test/t2v_metrics/R10: 31.204013377926422
MSRVTT_full_test/t2v_metrics/R50: 66.25418060200668
MSRVTT_full_test/t2v_metrics/MedR: 25.0
MSRVTT_full_test/t2v_metrics/MeanR: 76.18578595317726
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 13.815163162902147
MSRVTT_full_test/v2t_metrics/R1: 5.317725752508361
MSRVTT_full_test/v2t_metrics/R5: 21.103678929765888
MSRVTT_full_test/v2t_metrics/R10: 32.90969899665552
MSRVTT_full_test/v2t_metrics/R50: 68.56187290969899
MSRVTT_full_test/v2t_metrics/MedR: 23.0
MSRVTT_full_test/v2t_metrics/MeanR: 70.58043478260869
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 15.457384343666748
mnt_best : 13.815163162902147
not_improved_count: 0
Train Epoch: 9 [1/250 128/32000 (0%)] Loss: 1.97515 (semantic_loss: 0.02578, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=32.85489
Train Epoch: 9 [12/250 1536/32000 (5%)] Loss: 1.97281 (semantic_loss: 0.02247, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.33819
Train Epoch: 9 [23/250 2944/32000 (9%)] Loss: 1.97244 (semantic_loss: 0.02308, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.34938
Train Epoch: 9 [34/250 4352/32000 (14%)] Loss: 1.97305 (semantic_loss: 0.02271, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36190
Train Epoch: 9 [45/250 5760/32000 (18%)] Loss: 1.97264 (semantic_loss: 0.02328, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.37223
Train Epoch: 9 [56/250 7168/32000 (22%)] Loss: 1.97323 (semantic_loss: 0.02387, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33159
Train Epoch: 9 [67/250 8576/32000 (27%)] Loss: 1.97417 (semantic_loss: 0.02383, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34012
Train Epoch: 9 [78/250 9984/32000 (31%)] Loss: 1.97267 (semantic_loss: 0.02330, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=7.08008
Train Epoch: 9 [89/250 11392/32000 (36%)] Loss: 1.97249 (semantic_loss: 0.02215, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36193
Train Epoch: 9 [100/250 12800/32000 (40%)] Loss: 1.97280 (semantic_loss: 0.02246, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35073
Train Epoch: 9 [111/250 14208/32000 (44%)] Loss: 1.97480 (semantic_loss: 0.02446, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33929
Train Epoch: 9 [122/250 15616/32000 (49%)] Loss: 1.97358 (semantic_loss: 0.02324, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33674
Train Epoch: 9 [133/250 17024/32000 (53%)] Loss: 1.97418 (semantic_loss: 0.02482, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34165
Train Epoch: 9 [144/250 18432/32000 (58%)] Loss: 1.97325 (semantic_loss: 0.02292, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37140
Train Epoch: 9 [155/250 19840/32000 (62%)] Loss: 1.97279 (semantic_loss: 0.02342, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33560
Train Epoch: 9 [166/250 21248/32000 (66%)] Loss: 1.97037 (semantic_loss: 0.02101, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.36886
Train Epoch: 9 [177/250 22656/32000 (71%)] Loss: 1.97139 (semantic_loss: 0.02203, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.37724
Train Epoch: 9 [188/250 24064/32000 (75%)] Loss: 1.97406 (semantic_loss: 0.02372, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.38089
Train Epoch: 9 [199/250 25472/32000 (80%)] Loss: 1.97433 (semantic_loss: 0.02497, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35925
Train Epoch: 9 [210/250 26880/32000 (84%)] Loss: 1.97318 (semantic_loss: 0.02284, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35096
Train Epoch: 9 [221/250 28288/32000 (88%)] Loss: 1.97236 (semantic_loss: 0.02300, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35844
Train Epoch: 9 [232/250 29696/32000 (93%)] Loss: 1.97327 (semantic_loss: 0.02391, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35376
Train Epoch: 9 [243/250 31104/32000 (97%)] Loss: 1.97130 (semantic_loss: 0.02194, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34648
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch9.pth ...
Done in 6.962s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch9.pth ...
Done in 10.816s
removing stale ckpt [epoch 8] [took 0.01s]
epoch : 9
loss : 1.9731301808357238
learning_rate : 3.317102156445311e-05
n_samples : 288000
n_steps : 2250
MSRVTT_full_val/t2v_metrics/R1: 15.895372233400403
MSRVTT_full_val/t2v_metrics/R5: 51.10663983903421
MSRVTT_full_val/t2v_metrics/R10: 66.80080482897384
MSRVTT_full_val/t2v_metrics/R50: 92.5553319919517
MSRVTT_full_val/t2v_metrics/MedR: 5.0
MSRVTT_full_val/t2v_metrics/MeanR: 14.995975855130785
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 37.859648291482884
MSRVTT_full_val/v2t_metrics/R1: 14.285714285714286
MSRVTT_full_val/v2t_metrics/R5: 52.91750503018109
MSRVTT_full_val/v2t_metrics/R10: 70.62374245472837
MSRVTT_full_val/v2t_metrics/R50: 93.36016096579476
MSRVTT_full_val/v2t_metrics/MedR: 5.0
MSRVTT_full_val/v2t_metrics/MeanR: 13.545271629778671
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 37.65454023148374
MSRVTT_full_test/t2v_metrics/R1: 5.384615384615385
MSRVTT_full_test/t2v_metrics/R5: 19.297658862876254
MSRVTT_full_test/t2v_metrics/R10: 31.270903010033443
MSRVTT_full_test/t2v_metrics/R50: 67.32441471571906
MSRVTT_full_test/t2v_metrics/MedR: 25.0
MSRVTT_full_test/t2v_metrics/MeanR: 74.58896321070235
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 14.81152962988078
MSRVTT_full_test/v2t_metrics/R1: 5.384615384615385
MSRVTT_full_test/v2t_metrics/R5: 20.066889632107024
MSRVTT_full_test/v2t_metrics/R10: 31.77257525083612
MSRVTT_full_test/v2t_metrics/R50: 68.62876254180603
MSRVTT_full_test/v2t_metrics/MedR: 23.0
MSRVTT_full_test/v2t_metrics/MeanR: 70.24013377926421
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 15.085593082316395
mnt_best : 14.81152962988078
not_improved_count: 0
Train Epoch: 10 [1/250 128/32000 (0%)] Loss: 1.97240 (semantic_loss: 0.02206, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=31.74078
Train Epoch: 10 [12/250 1536/32000 (5%)] Loss: 1.97277 (semantic_loss: 0.02243, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=3.19361
Train Epoch: 10 [23/250 2944/32000 (9%)] Loss: 1.97282 (semantic_loss: 0.02346, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=1.04536
Train Epoch: 10 [34/250 4352/32000 (14%)] Loss: 1.97405 (semantic_loss: 0.02371, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34694
Train Epoch: 10 [45/250 5760/32000 (18%)] Loss: 1.97367 (semantic_loss: 0.02333, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34413
Train Epoch: 10 [56/250 7168/32000 (22%)] Loss: 1.97157 (semantic_loss: 0.02221, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33709
Train Epoch: 10 [67/250 8576/32000 (27%)] Loss: 1.97265 (semantic_loss: 0.02329, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34402
Train Epoch: 10 [78/250 9984/32000 (31%)] Loss: 1.97191 (semantic_loss: 0.02158, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33395
Train Epoch: 10 [89/250 11392/32000 (36%)] Loss: 1.97185 (semantic_loss: 0.02151, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33448
Train Epoch: 10 [100/250 12800/32000 (40%)] Loss: 1.97019 (semantic_loss: 0.02083, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33371
Train Epoch: 10 [111/250 14208/32000 (44%)] Loss: 1.96975 (semantic_loss: 0.02039, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33864
Train Epoch: 10 [122/250 15616/32000 (49%)] Loss: 1.97459 (semantic_loss: 0.02328, quant_loss: 1.95117, bit_balance_loss: 0.00014) batch_time=0.36273
Train Epoch: 10 [133/250 17024/32000 (53%)] Loss: 1.97258 (semantic_loss: 0.02322, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34495
Train Epoch: 10 [144/250 18432/32000 (58%)] Loss: 1.97313 (semantic_loss: 0.02279, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=2.39725
Train Epoch: 10 [155/250 19840/32000 (62%)] Loss: 1.97129 (semantic_loss: 0.02095, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34853
Train Epoch: 10 [166/250 21248/32000 (66%)] Loss: 1.97055 (semantic_loss: 0.02119, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.36199
Train Epoch: 10 [177/250 22656/32000 (71%)] Loss: 1.97235 (semantic_loss: 0.02202, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.39321
Train Epoch: 10 [188/250 24064/32000 (75%)] Loss: 1.97018 (semantic_loss: 0.02082, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34234
Train Epoch: 10 [199/250 25472/32000 (80%)] Loss: 1.97114 (semantic_loss: 0.02080, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.33292
Train Epoch: 10 [210/250 26880/32000 (84%)] Loss: 1.97488 (semantic_loss: 0.02455, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.38122
Train Epoch: 10 [221/250 28288/32000 (88%)] Loss: 1.97254 (semantic_loss: 0.02318, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35268
Train Epoch: 10 [232/250 29696/32000 (93%)] Loss: 1.97222 (semantic_loss: 0.02189, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.56155
Train Epoch: 10 [243/250 31104/32000 (97%)] Loss: 1.97267 (semantic_loss: 0.02233, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34966
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch10.pth ...
Done in 4.566s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch10.pth ...
Done in 8.653s
removing stale ckpt [epoch 9] [took 0.00s]
epoch : 10
loss : 1.9722250061035156
learning_rate : 3.151247048623045e-05
n_samples : 320000
n_steps : 2500
MSRVTT_full_val/t2v_metrics/R1: 15.694164989939638
MSRVTT_full_val/t2v_metrics/R5: 48.69215291750503
MSRVTT_full_val/t2v_metrics/R10: 67.6056338028169
MSRVTT_full_val/t2v_metrics/R50: 94.36619718309859
MSRVTT_full_val/t2v_metrics/MedR: 6.0
MSRVTT_full_val/t2v_metrics/MeanR: 14.777665995975855
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 37.244318045316845
MSRVTT_full_val/v2t_metrics/R1: 16.29778672032193
MSRVTT_full_val/v2t_metrics/R5: 53.118712273641854
MSRVTT_full_val/v2t_metrics/R10: 70.02012072434607
MSRVTT_full_val/v2t_metrics/R50: 94.56740442655935
MSRVTT_full_val/v2t_metrics/MedR: 5.0
MSRVTT_full_val/v2t_metrics/MeanR: 12.714285714285714
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 39.28255022953261
MSRVTT_full_test/t2v_metrics/R1: 5.351170568561873
MSRVTT_full_test/t2v_metrics/R5: 20.03344481605351
MSRVTT_full_test/t2v_metrics/R10: 30.869565217391305
MSRVTT_full_test/t2v_metrics/R50: 66.92307692307692
MSRVTT_full_test/t2v_metrics/MedR: 25.0
MSRVTT_full_test/t2v_metrics/MeanR: 77.8314381270903
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 14.902014456276266
MSRVTT_full_test/v2t_metrics/R1: 5.217391304347826
MSRVTT_full_test/v2t_metrics/R5: 21.270903010033443
MSRVTT_full_test/v2t_metrics/R10: 32.07357859531773
MSRVTT_full_test/v2t_metrics/R50: 68.29431438127091
MSRVTT_full_test/v2t_metrics/MedR: 23.0
MSRVTT_full_test/v2t_metrics/MeanR: 69.61488294314381
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 15.268472295576558
mnt_best : 14.902014456276266
not_improved_count: 0
Train Epoch: 11 [1/250 128/32000 (0%)] Loss: 1.97218 (semantic_loss: 0.02185, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=34.23220
Train Epoch: 11 [12/250 1536/32000 (5%)] Loss: 1.97282 (semantic_loss: 0.02248, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.39298
Train Epoch: 11 [23/250 2944/32000 (9%)] Loss: 1.97067 (semantic_loss: 0.02131, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35307
Train Epoch: 11 [34/250 4352/32000 (14%)] Loss: 1.97232 (semantic_loss: 0.02199, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37068
Train Epoch: 11 [45/250 5760/32000 (18%)] Loss: 1.96858 (semantic_loss: 0.02019, quant_loss: 1.94824, bit_balance_loss: 0.00014) batch_time=0.34110
Train Epoch: 11 [56/250 7168/32000 (22%)] Loss: 1.97203 (semantic_loss: 0.02169, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34754
Train Epoch: 11 [67/250 8576/32000 (27%)] Loss: 1.96819 (semantic_loss: 0.01882, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35905
Train Epoch: 11 [78/250 9984/32000 (31%)] Loss: 1.97304 (semantic_loss: 0.02172, quant_loss: 1.95117, bit_balance_loss: 0.00014) batch_time=0.32928
Train Epoch: 11 [89/250 11392/32000 (36%)] Loss: 1.97272 (semantic_loss: 0.02335, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34007
Train Epoch: 11 [100/250 12800/32000 (40%)] Loss: 1.97342 (semantic_loss: 0.02308, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33310
Train Epoch: 11 [111/250 14208/32000 (44%)] Loss: 1.97102 (semantic_loss: 0.02166, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35619
Train Epoch: 11 [122/250 15616/32000 (49%)] Loss: 1.97187 (semantic_loss: 0.02153, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36933
Train Epoch: 11 [133/250 17024/32000 (53%)] Loss: 1.97202 (semantic_loss: 0.02168, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.32800
Train Epoch: 11 [144/250 18432/32000 (58%)] Loss: 1.97240 (semantic_loss: 0.02206, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35474
Train Epoch: 11 [155/250 19840/32000 (62%)] Loss: 1.97162 (semantic_loss: 0.02226, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.38055
Train Epoch: 11 [166/250 21248/32000 (66%)] Loss: 1.97183 (semantic_loss: 0.02150, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.38986
Train Epoch: 11 [177/250 22656/32000 (71%)] Loss: 1.97097 (semantic_loss: 0.02161, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34697
Train Epoch: 11 [188/250 24064/32000 (75%)] Loss: 1.97369 (semantic_loss: 0.02237, quant_loss: 1.95117, bit_balance_loss: 0.00014) batch_time=0.34811
Train Epoch: 11 [199/250 25472/32000 (80%)] Loss: 1.97481 (semantic_loss: 0.02448, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35140
Train Epoch: 11 [210/250 26880/32000 (84%)] Loss: 1.97118 (semantic_loss: 0.02182, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33276
Train Epoch: 11 [221/250 28288/32000 (88%)] Loss: 1.97162 (semantic_loss: 0.02129, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34076
Train Epoch: 11 [232/250 29696/32000 (93%)] Loss: 1.97246 (semantic_loss: 0.02212, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34741
Train Epoch: 11 [243/250 31104/32000 (97%)] Loss: 1.97055 (semantic_loss: 0.02119, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34644
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch11.pth ...
Done in 18.228s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch11.pth ...
Done in 22.306s
removing stale ckpt [epoch 10] [took 0.00s]
epoch : 11
loss : 1.9714753336906432
learning_rate : 2.993684696191893e-05
n_samples : 352000
n_steps : 2750
MSRVTT_full_val/t2v_metrics/R1: 17.706237424547282
MSRVTT_full_val/t2v_metrics/R5: 53.31991951710262
MSRVTT_full_val/t2v_metrics/R10: 68.41046277665995
MSRVTT_full_val/t2v_metrics/R50: 93.56136820925553
MSRVTT_full_val/t2v_metrics/MedR: 5.0
MSRVTT_full_val/t2v_metrics/MeanR: 14.396378269617706
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 40.12170979660853
MSRVTT_full_val/v2t_metrics/R1: 16.498993963782695
MSRVTT_full_val/v2t_metrics/R5: 55.1307847082495
MSRVTT_full_val/v2t_metrics/R10: 69.61770623742454
MSRVTT_full_val/v2t_metrics/R50: 93.36016096579476
MSRVTT_full_val/v2t_metrics/MedR: 5.0
MSRVTT_full_val/v2t_metrics/MeanR: 12.938631790744466
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 39.85875989537627
MSRVTT_full_test/t2v_metrics/R1: 6.187290969899665
MSRVTT_full_test/t2v_metrics/R5: 21.337792642140467
MSRVTT_full_test/t2v_metrics/R10: 33.47826086956522
MSRVTT_full_test/t2v_metrics/R50: 68.29431438127091
MSRVTT_full_test/t2v_metrics/MedR: 22.0
MSRVTT_full_test/t2v_metrics/MeanR: 74.83578595317725
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 16.411098036630644
MSRVTT_full_test/v2t_metrics/R1: 5.919732441471572
MSRVTT_full_test/v2t_metrics/R5: 23.244147157190636
MSRVTT_full_test/v2t_metrics/R10: 34.81605351170568
MSRVTT_full_test/v2t_metrics/R50: 69.93311036789298
MSRVTT_full_test/v2t_metrics/MedR: 21.5
MSRVTT_full_test/v2t_metrics/MeanR: 67.8953177257525
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 16.857703531288102
mnt_best : 16.411098036630644
not_improved_count: 0
Train Epoch: 12 [1/250 128/32000 (0%)] Loss: 1.97078 (semantic_loss: 0.02142, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=29.48307
Train Epoch: 12 [12/250 1536/32000 (5%)] Loss: 1.97242 (semantic_loss: 0.02305, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.34048
Train Epoch: 12 [23/250 2944/32000 (9%)] Loss: 1.97043 (semantic_loss: 0.02107, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.34299
Train Epoch: 12 [34/250 4352/32000 (14%)] Loss: 1.97048 (semantic_loss: 0.02112, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.34763
Train Epoch: 12 [45/250 5760/32000 (18%)] Loss: 1.97197 (semantic_loss: 0.02163, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37887
Train Epoch: 12 [56/250 7168/32000 (22%)] Loss: 1.97152 (semantic_loss: 0.02119, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34872
Train Epoch: 12 [67/250 8576/32000 (27%)] Loss: 1.97007 (semantic_loss: 0.02071, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.36886
Train Epoch: 12 [78/250 9984/32000 (31%)] Loss: 1.97133 (semantic_loss: 0.02099, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33002
Train Epoch: 12 [89/250 11392/32000 (36%)] Loss: 1.97102 (semantic_loss: 0.02068, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33059
Train Epoch: 12 [100/250 12800/32000 (40%)] Loss: 1.97129 (semantic_loss: 0.02096, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33796
Train Epoch: 12 [111/250 14208/32000 (44%)] Loss: 1.97111 (semantic_loss: 0.02078, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36189
Train Epoch: 12 [122/250 15616/32000 (49%)] Loss: 1.97136 (semantic_loss: 0.02200, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34265
Train Epoch: 12 [133/250 17024/32000 (53%)] Loss: 1.97031 (semantic_loss: 0.02094, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.33285
Train Epoch: 12 [144/250 18432/32000 (58%)] Loss: 1.96926 (semantic_loss: 0.01989, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.36877
Train Epoch: 12 [155/250 19840/32000 (62%)] Loss: 1.97021 (semantic_loss: 0.02085, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.37035
Train Epoch: 12 [166/250 21248/32000 (66%)] Loss: 1.96906 (semantic_loss: 0.01970, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33351
Train Epoch: 12 [177/250 22656/32000 (71%)] Loss: 1.97020 (semantic_loss: 0.02084, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34093
Train Epoch: 12 [188/250 24064/32000 (75%)] Loss: 1.96914 (semantic_loss: 0.01978, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34833
Train Epoch: 12 [199/250 25472/32000 (80%)] Loss: 1.97087 (semantic_loss: 0.02053, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33680
Train Epoch: 12 [210/250 26880/32000 (84%)] Loss: 1.96978 (semantic_loss: 0.01944, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=3.70390
Train Epoch: 12 [221/250 28288/32000 (88%)] Loss: 1.97070 (semantic_loss: 0.02036, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36555
Train Epoch: 12 [232/250 29696/32000 (93%)] Loss: 1.96978 (semantic_loss: 0.02042, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35053
Train Epoch: 12 [243/250 31104/32000 (97%)] Loss: 1.97088 (semantic_loss: 0.02152, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.38595
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch12.pth ...
Done in 18.046s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch12.pth ...
Done in 22.189s
removing stale ckpt [epoch 11] [took 0.01s]
epoch : 12
loss : 1.9707341833114624
learning_rate : 2.844000461382298e-05
n_samples : 384000
n_steps : 3000
MSRVTT_full_val/t2v_metrics/R1: 20.72434607645875
MSRVTT_full_val/t2v_metrics/R5: 56.94164989939638
MSRVTT_full_val/t2v_metrics/R10: 72.23340040241449
MSRVTT_full_val/t2v_metrics/R50: 94.76861167002012
MSRVTT_full_val/t2v_metrics/MedR: 5.0
MSRVTT_full_val/t2v_metrics/MeanR: 12.486921529175051
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 44.00982559702672
MSRVTT_full_val/v2t_metrics/R1: 18.91348088531187
MSRVTT_full_val/v2t_metrics/R5: 58.14889336016097
MSRVTT_full_val/v2t_metrics/R10: 73.2394366197183
MSRVTT_full_val/v2t_metrics/R50: 94.36619718309859
MSRVTT_full_val/v2t_metrics/MedR: 4.0
MSRVTT_full_val/v2t_metrics/MeanR: 11.94466800804829
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 43.186960348349544
MSRVTT_full_test/t2v_metrics/R1: 5.88628762541806
MSRVTT_full_test/t2v_metrics/R5: 22.775919732441473
MSRVTT_full_test/t2v_metrics/R10: 35.65217391304348
MSRVTT_full_test/t2v_metrics/R50: 71.23745819397993
MSRVTT_full_test/t2v_metrics/MedR: 20.0
MSRVTT_full_test/t2v_metrics/MeanR: 65.57307692307693
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 16.844875539200718
MSRVTT_full_test/v2t_metrics/R1: 6.321070234113712
MSRVTT_full_test/v2t_metrics/R5: 23.54515050167224
MSRVTT_full_test/v2t_metrics/R10: 36.65551839464883
MSRVTT_full_test/v2t_metrics/R50: 71.97324414715719
MSRVTT_full_test/v2t_metrics/MedR: 18.5
MSRVTT_full_test/v2t_metrics/MeanR: 62.45836120401338
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 17.603964502679943
mnt_best : 16.844875539200718
not_improved_count: 0
Train Epoch: 13 [1/250 128/32000 (0%)] Loss: 1.97172 (semantic_loss: 0.02236, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=33.15875
Train Epoch: 13 [12/250 1536/32000 (5%)] Loss: 1.97003 (semantic_loss: 0.02067, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35023
Train Epoch: 13 [23/250 2944/32000 (9%)] Loss: 1.96972 (semantic_loss: 0.02134, quant_loss: 1.94824, bit_balance_loss: 0.00014) batch_time=0.38180
Train Epoch: 13 [34/250 4352/32000 (14%)] Loss: 1.97013 (semantic_loss: 0.01979, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37153
Train Epoch: 13 [45/250 5760/32000 (18%)] Loss: 1.97053 (semantic_loss: 0.02019, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37127
Train Epoch: 13 [56/250 7168/32000 (22%)] Loss: 1.96978 (semantic_loss: 0.02042, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33735
Train Epoch: 13 [67/250 8576/32000 (27%)] Loss: 1.96803 (semantic_loss: 0.01867, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33932
Train Epoch: 13 [78/250 9984/32000 (31%)] Loss: 1.96926 (semantic_loss: 0.01990, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34761
Train Epoch: 13 [89/250 11392/32000 (36%)] Loss: 1.97059 (semantic_loss: 0.02026, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34849
Train Epoch: 13 [100/250 12800/32000 (40%)] Loss: 1.97087 (semantic_loss: 0.02053, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34284
Train Epoch: 13 [111/250 14208/32000 (44%)] Loss: 1.96945 (semantic_loss: 0.01911, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36142
Train Epoch: 13 [122/250 15616/32000 (49%)] Loss: 1.97094 (semantic_loss: 0.02061, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.40638
Train Epoch: 13 [133/250 17024/32000 (53%)] Loss: 1.96948 (semantic_loss: 0.01914, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35133
Train Epoch: 13 [144/250 18432/32000 (58%)] Loss: 1.97062 (semantic_loss: 0.02028, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=2.73428
Train Epoch: 13 [155/250 19840/32000 (62%)] Loss: 1.96914 (semantic_loss: 0.01978, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.38852
Train Epoch: 13 [166/250 21248/32000 (66%)] Loss: 1.97008 (semantic_loss: 0.02072, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34396
Train Epoch: 13 [177/250 22656/32000 (71%)] Loss: 1.96984 (semantic_loss: 0.02047, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.32936
Train Epoch: 13 [188/250 24064/32000 (75%)] Loss: 1.97048 (semantic_loss: 0.02015, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33931
Train Epoch: 13 [199/250 25472/32000 (80%)] Loss: 1.96859 (semantic_loss: 0.01923, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=1.97124
Train Epoch: 13 [210/250 26880/32000 (84%)] Loss: 1.96970 (semantic_loss: 0.02034, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34053
Train Epoch: 13 [221/250 28288/32000 (88%)] Loss: 1.97099 (semantic_loss: 0.02066, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36918
Train Epoch: 13 [232/250 29696/32000 (93%)] Loss: 1.97090 (semantic_loss: 0.02154, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.86897
Train Epoch: 13 [243/250 31104/32000 (97%)] Loss: 1.97136 (semantic_loss: 0.02102, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33735
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch13.pth ...
Done in 4.545s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch13.pth ...
Done in 8.437s
removing stale ckpt [epoch 12] [took 0.00s]
epoch : 13
loss : 1.9701430792808532
learning_rate : 2.7018004383131832e-05
n_samples : 416000
n_steps : 3250
MSRVTT_full_val/t2v_metrics/R1: 19.114688128772634
MSRVTT_full_val/t2v_metrics/R5: 55.734406438631794
MSRVTT_full_val/t2v_metrics/R10: 71.42857142857143
MSRVTT_full_val/t2v_metrics/R50: 94.16498993963782
MSRVTT_full_val/t2v_metrics/MedR: 4.0
MSRVTT_full_val/t2v_metrics/MeanR: 12.203219315895373
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 42.37608721287829
MSRVTT_full_val/v2t_metrics/R1: 20.523138832997986
MSRVTT_full_val/v2t_metrics/R5: 60.160965794768615
MSRVTT_full_val/v2t_metrics/R10: 73.44064386317908
MSRVTT_full_val/v2t_metrics/R50: 95.17102615694165
MSRVTT_full_val/v2t_metrics/MedR: 4.0
MSRVTT_full_val/v2t_metrics/MeanR: 11.299798792756539
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 44.926062068350376
MSRVTT_full_test/t2v_metrics/R1: 6.086956521739131
MSRVTT_full_test/t2v_metrics/R5: 24.08026755852843
MSRVTT_full_test/t2v_metrics/R10: 35.585284280936456
MSRVTT_full_test/t2v_metrics/R50: 72.10702341137124
MSRVTT_full_test/t2v_metrics/MedR: 20.0
MSRVTT_full_test/t2v_metrics/MeanR: 65.13294314381271
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 17.34245790961053
MSRVTT_full_test/v2t_metrics/R1: 7.357859531772576
MSRVTT_full_test/v2t_metrics/R5: 25.953177257525084
MSRVTT_full_test/v2t_metrics/R10: 39.63210702341137
MSRVTT_full_test/v2t_metrics/R50: 75.25083612040133
MSRVTT_full_test/v2t_metrics/MedR: 16.5
MSRVTT_full_test/v2t_metrics/MeanR: 57.671571906354515
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 19.633439831017117
mnt_best : 17.34245790961053
not_improved_count: 0
Train Epoch: 14 [1/250 128/32000 (0%)] Loss: 1.96999 (semantic_loss: 0.02063, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=40.18106
Train Epoch: 14 [12/250 1536/32000 (5%)] Loss: 1.96999 (semantic_loss: 0.02063, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33476
Train Epoch: 14 [23/250 2944/32000 (9%)] Loss: 1.97107 (semantic_loss: 0.02074, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33745
Train Epoch: 14 [34/250 4352/32000 (14%)] Loss: 1.96941 (semantic_loss: 0.02005, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35067
Train Epoch: 14 [45/250 5760/32000 (18%)] Loss: 1.96932 (semantic_loss: 0.01899, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34775
Train Epoch: 14 [56/250 7168/32000 (22%)] Loss: 1.97051 (semantic_loss: 0.02115, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34777
Train Epoch: 14 [67/250 8576/32000 (27%)] Loss: 1.96886 (semantic_loss: 0.01950, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35218
Train Epoch: 14 [78/250 9984/32000 (31%)] Loss: 1.97085 (semantic_loss: 0.02052, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33039
Train Epoch: 14 [89/250 11392/32000 (36%)] Loss: 1.96953 (semantic_loss: 0.02017, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.38448
Train Epoch: 14 [100/250 12800/32000 (40%)] Loss: 1.97148 (semantic_loss: 0.02115, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33253
Train Epoch: 14 [111/250 14208/32000 (44%)] Loss: 1.96887 (semantic_loss: 0.01854, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.44364
Train Epoch: 14 [122/250 15616/32000 (49%)] Loss: 1.96827 (semantic_loss: 0.01891, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33555
Train Epoch: 14 [133/250 17024/32000 (53%)] Loss: 1.96971 (semantic_loss: 0.01937, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37228
Train Epoch: 14 [144/250 18432/32000 (58%)] Loss: 1.97252 (semantic_loss: 0.02218, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34981
Train Epoch: 14 [155/250 19840/32000 (62%)] Loss: 1.97068 (semantic_loss: 0.02034, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35826
Train Epoch: 14 [166/250 21248/32000 (66%)] Loss: 1.96797 (semantic_loss: 0.01861, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.47345
Train Epoch: 14 [177/250 22656/32000 (71%)] Loss: 1.97020 (semantic_loss: 0.01985, quant_loss: 1.95020, bit_balance_loss: 0.00015) batch_time=0.34218
Train Epoch: 14 [188/250 24064/32000 (75%)] Loss: 1.96762 (semantic_loss: 0.01826, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33970
Train Epoch: 14 [199/250 25472/32000 (80%)] Loss: 1.97018 (semantic_loss: 0.01984, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.38331
Train Epoch: 14 [210/250 26880/32000 (84%)] Loss: 1.96831 (semantic_loss: 0.01895, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.32934
Train Epoch: 14 [221/250 28288/32000 (88%)] Loss: 1.96985 (semantic_loss: 0.01951, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33266
Train Epoch: 14 [232/250 29696/32000 (93%)] Loss: 1.97039 (semantic_loss: 0.02102, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.32945
Train Epoch: 14 [243/250 31104/32000 (97%)] Loss: 1.96962 (semantic_loss: 0.01928, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34751
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch14.pth ...
Done in 4.114s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch14.pth ...
Done in 8.917s
removing stale ckpt [epoch 13] [took 0.00s]
epoch : 14
loss : 1.9695526356697082
learning_rate : 2.566710416397524e-05
n_samples : 448000
n_steps : 3500
MSRVTT_full_val/t2v_metrics/R1: 17.505030181086518
MSRVTT_full_val/t2v_metrics/R5: 56.74044265593562
MSRVTT_full_val/t2v_metrics/R10: 70.62374245472837
MSRVTT_full_val/t2v_metrics/R50: 93.36016096579476
MSRVTT_full_val/t2v_metrics/MedR: 5.0
MSRVTT_full_val/t2v_metrics/MeanR: 13.8158953722334
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 41.24159347959206
MSRVTT_full_val/v2t_metrics/R1: 21.327967806841045
MSRVTT_full_val/v2t_metrics/R5: 58.75251509054326
MSRVTT_full_val/v2t_metrics/R10: 73.03822937625755
MSRVTT_full_val/v2t_metrics/R50: 94.56740442655935
MSRVTT_full_val/v2t_metrics/MedR: 4.0
MSRVTT_full_val/v2t_metrics/MeanR: 11.865191146881287
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 45.06527841685346
MSRVTT_full_test/t2v_metrics/R1: 6.521739130434782
MSRVTT_full_test/t2v_metrics/R5: 23.17725752508361
MSRVTT_full_test/t2v_metrics/R10: 35.11705685618729
MSRVTT_full_test/t2v_metrics/R50: 70.5685618729097
MSRVTT_full_test/t2v_metrics/MedR: 20.75
MSRVTT_full_test/t2v_metrics/MeanR: 72.27140468227425
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 17.44407157737787
MSRVTT_full_test/v2t_metrics/R1: 6.7558528428093645
MSRVTT_full_test/v2t_metrics/R5: 24.347826086956523
MSRVTT_full_test/v2t_metrics/R10: 37.357859531772576
MSRVTT_full_test/v2t_metrics/R50: 72.3076923076923
MSRVTT_full_test/v2t_metrics/MedR: 18.0
MSRVTT_full_test/v2t_metrics/MeanR: 65.59749163879599
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 18.316428105436536
mnt_best : 17.44407157737787
not_improved_count: 0
Train Epoch: 15 [1/250 128/32000 (0%)] Loss: 1.97179 (semantic_loss: 0.02146, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=32.77202
Train Epoch: 15 [12/250 1536/32000 (5%)] Loss: 1.96953 (semantic_loss: 0.01920, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35121
Train Epoch: 15 [23/250 2944/32000 (9%)] Loss: 1.97126 (semantic_loss: 0.02093, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.38289
Train Epoch: 15 [34/250 4352/32000 (14%)] Loss: 1.96801 (semantic_loss: 0.01864, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34288
Train Epoch: 15 [45/250 5760/32000 (18%)] Loss: 1.96913 (semantic_loss: 0.01977, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34920
Train Epoch: 15 [56/250 7168/32000 (22%)] Loss: 1.96953 (semantic_loss: 0.01920, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.37347
Train Epoch: 15 [67/250 8576/32000 (27%)] Loss: 1.96944 (semantic_loss: 0.01911, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34354
Train Epoch: 15 [78/250 9984/32000 (31%)] Loss: 1.97071 (semantic_loss: 0.01940, quant_loss: 1.95117, bit_balance_loss: 0.00014) batch_time=0.36537
Train Epoch: 15 [89/250 11392/32000 (36%)] Loss: 1.97005 (semantic_loss: 0.01971, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34690
Train Epoch: 15 [100/250 12800/32000 (40%)] Loss: 1.96870 (semantic_loss: 0.01836, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33870
Train Epoch: 15 [111/250 14208/32000 (44%)] Loss: 1.96991 (semantic_loss: 0.01957, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.38632
Train Epoch: 15 [122/250 15616/32000 (49%)] Loss: 1.96752 (semantic_loss: 0.01816, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33836
Train Epoch: 15 [133/250 17024/32000 (53%)] Loss: 1.97072 (semantic_loss: 0.02038, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.36839
Train Epoch: 15 [144/250 18432/32000 (58%)] Loss: 1.96988 (semantic_loss: 0.01955, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.35068
Train Epoch: 15 [155/250 19840/32000 (62%)] Loss: 1.96927 (semantic_loss: 0.01894, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34753
Train Epoch: 15 [166/250 21248/32000 (66%)] Loss: 1.96651 (semantic_loss: 0.01715, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34780
Train Epoch: 15 [177/250 22656/32000 (71%)] Loss: 1.97049 (semantic_loss: 0.01918, quant_loss: 1.95117, bit_balance_loss: 0.00015) batch_time=0.38041
Train Epoch: 15 [188/250 24064/32000 (75%)] Loss: 1.97012 (semantic_loss: 0.02076, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34772
Train Epoch: 15 [199/250 25472/32000 (80%)] Loss: 1.97116 (semantic_loss: 0.02180, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33049
Train Epoch: 15 [210/250 26880/32000 (84%)] Loss: 1.96978 (semantic_loss: 0.02042, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34599
Train Epoch: 15 [221/250 28288/32000 (88%)] Loss: 1.96897 (semantic_loss: 0.01863, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.34211
Train Epoch: 15 [232/250 29696/32000 (93%)] Loss: 1.96837 (semantic_loss: 0.01901, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.36693
Train Epoch: 15 [243/250 31104/32000 (97%)] Loss: 1.96779 (semantic_loss: 0.01843, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.54816
Saving checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch15.pth ...
Done in 4.034s
Updating 'best' checkpoint: /apdcephfs/share_47076/gimwang/HCQ/exps/DCMH_MSRVTT_full/checkpoint-epoch15.pth ...
Done in 8.334s
removing stale ckpt [epoch 14] [took 0.02s]
epoch : 15
loss : 1.9691570582389832
learning_rate : 2.4383748955776477e-05
n_samples : 480000
n_steps : 3750
MSRVTT_full_val/t2v_metrics/R1: 21.327967806841045
MSRVTT_full_val/t2v_metrics/R5: 56.33802816901409
MSRVTT_full_val/t2v_metrics/R10: 71.42857142857143
MSRVTT_full_val/t2v_metrics/R50: 94.56740442655935
MSRVTT_full_val/t2v_metrics/MedR: 4.0
MSRVTT_full_val/t2v_metrics/MeanR: 13.030181086519114
MSRVTT_full_val/t2v_metrics/geometric_mean_R1-R5-R10: 44.11040322724108
MSRVTT_full_val/v2t_metrics/R1: 22.93762575452716
MSRVTT_full_val/v2t_metrics/R5: 59.758551307847085
MSRVTT_full_val/v2t_metrics/R10: 73.03822937625755
MSRVTT_full_val/v2t_metrics/R50: 95.17102615694165
MSRVTT_full_val/v2t_metrics/MedR: 4.0
MSRVTT_full_val/v2t_metrics/MeanR: 11.800804828973844
MSRVTT_full_val/v2t_metrics/geometric_mean_R1-R5-R10: 46.43366029918887
MSRVTT_full_test/t2v_metrics/R1: 6.923076923076923
MSRVTT_full_test/t2v_metrics/R5: 24.214046822742475
MSRVTT_full_test/t2v_metrics/R10: 37.290969899665555
MSRVTT_full_test/t2v_metrics/R50: 72.14046822742475
MSRVTT_full_test/t2v_metrics/MedR: 18.0
MSRVTT_full_test/t2v_metrics/MeanR: 66.21270903010033
MSRVTT_full_test/t2v_metrics/geometric_mean_R1-R5-R10: 18.421432737983213
MSRVTT_full_test/v2t_metrics/R1: 7.6923076923076925
MSRVTT_full_test/v2t_metrics/R5: 26.588628762541806
MSRVTT_full_test/v2t_metrics/R10: 39.7324414715719
MSRVTT_full_test/v2t_metrics/R50: 73.67892976588628
MSRVTT_full_test/v2t_metrics/MedR: 17.0
MSRVTT_full_test/v2t_metrics/MeanR: 62.97458193979933
MSRVTT_full_test/v2t_metrics/geometric_mean_R1-R5-R10: 20.104777916454005
mnt_best : 18.421432737983213
not_improved_count: 0
Train Epoch: 16 [1/250 128/32000 (0%)] Loss: 1.96868 (semantic_loss: 0.01933, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=31.68989
Train Epoch: 16 [12/250 1536/32000 (5%)] Loss: 1.96745 (semantic_loss: 0.01809, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.33824
Train Epoch: 16 [23/250 2944/32000 (9%)] Loss: 1.96891 (semantic_loss: 0.01954, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.34738
Train Epoch: 16 [34/250 4352/32000 (14%)] Loss: 1.96822 (semantic_loss: 0.01886, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35562
Train Epoch: 16 [45/250 5760/32000 (18%)] Loss: 1.96878 (semantic_loss: 0.01942, quant_loss: 1.94922, bit_balance_loss: 0.00014) batch_time=0.35744
Train Epoch: 16 [56/250 7168/32000 (22%)] Loss: 1.96825 (semantic_loss: 0.01889, quant_loss: 1.94922, bit_balance_loss: 0.00015) batch_time=0.35561
Train Epoch: 16 [67/250 8576/32000 (27%)] Loss: 1.96865 (semantic_loss: 0.01831, quant_loss: 1.95020, bit_balance_loss: 0.00014) batch_time=0.33167