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ssv2_large_aq_2clip.log
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ssv2_large_aq_2clip.log
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=> dataset: somethingv2
=> root_path: /tmp/
=> num_classes: 174
Initializing RubiksNet-Large variant "rubiks3d-aq". num_frames=8
RubiksNet attention shift (before block.conv2)
=> setup forward prop for temporal attention shift
=> tier: large
=> variant: attention
=> eval mode: 2-clip
video 0 done, total 0/24777, average 0.819 sec/video, moving Prec@1 67.500 Prec@5 91.250
video 1600 done, total 1600/24777, average 0.062 sec/video, moving Prec@1 61.905 Prec@5 86.131
video 3200 done, total 3200/24777, average 0.041 sec/video, moving Prec@1 62.134 Prec@5 86.616
video 4800 done, total 4800/24777, average 0.035 sec/video, moving Prec@1 61.107 Prec@5 86.230
video 6400 done, total 6400/24777, average 0.033 sec/video, moving Prec@1 61.080 Prec@5 86.157
video 8000 done, total 8000/24777, average 0.031 sec/video, moving Prec@1 60.953 Prec@5 86.077
video 9600 done, total 9600/24777, average 0.030 sec/video, moving Prec@1 61.240 Prec@5 86.281
video 11200 done, total 11200/24777, average 0.029 sec/video, moving Prec@1 61.534 Prec@5 86.489
video 12800 done, total 12800/24777, average 0.028 sec/video, moving Prec@1 61.607 Prec@5 86.491
video 14400 done, total 14400/24777, average 0.028 sec/video, moving Prec@1 61.623 Prec@5 86.713
video 16000 done, total 16000/24777, average 0.027 sec/video, moving Prec@1 61.567 Prec@5 86.636
video 17600 done, total 17600/24777, average 0.027 sec/video, moving Prec@1 61.408 Prec@5 86.482
video 19200 done, total 19200/24777, average 0.027 sec/video, moving Prec@1 61.473 Prec@5 86.483
video 20800 done, total 20800/24777, average 0.027 sec/video, moving Prec@1 61.557 Prec@5 86.557
video 22400 done, total 22400/24777, average 0.027 sec/video, moving Prec@1 61.535 Prec@5 86.610
video 24000 done, total 24000/24777, average 0.026 sec/video, moving Prec@1 61.507 Prec@5 86.599
====================== Evaluation Complete ======================
Class confusion matrix:
[0.90517241 0.48684211 0.39215686 0.6407767 0.48717949 0.60964912
0.80095923 0.54545455 0.5984252 0.70198675 0.66292135 0.70072993
0.35042735 0.4 0.78947368 0.51489362 0.3248731 0.41447368
0.49372385 0.6492891 0.54724409 0.64035088 0.45930233 0.56382979
0.61363636 0.47368421 0.475 0.45544554 0.73636364 0.8045977
0.83783784 0.79279279 0.84090909 0.16504854 0.20481928 0.09375
0.84331797 0.81368821 0.14814815 0.67647059 0.7431694 0.64285714
0.68075117 0.60450161 0.67567568 0.57938719 0.5813253 0.49246231
0.40993789 0.88172043 0.7721519 0.13333333 0.28125 0.71428571
0.5 0.39333333 0.43150685 0.6509434 0.17647059 0.79496403
0.8 0.23529412 0.78481013 0.20560748 0.21621622 0.64150943
0.29245283 0.48258706 0.70175439 0.39 0.58928571 0.39130435
0.58823529 0.64102564 0.70754717 0.31578947 0.27777778 0.42307692
0.22222222 0.77586207 0.3125 0.144 0.36170213 0.46808511
0.6 0.55555556 0.79411765 0.856 0.29166667 0.08433735
0.44927536 0.9 0.54385965 0.82 0.80932203 0.19444444
0.11764706 0.24793388 0.66326531 0.75457875 0.53584906 0.72527473
0.25862069 0.76785714 0.77165354 0.78518519 0.5890411 0.69950739
0.36486486 0.54333333 0.63380282 0. 0.5323741 0.33333333
0.71875 0.54347826 0.53703704 0.75396825 0.42372881 0.67326733
0.75590551 0.78409091 0.31034483 0.63076923 0.46153846 0.6146789
0.50485437 0.46956522 0.16858238 0.67647059 0.35 0.21917808
0.49425287 0.24561404 0.83152174 0.55214724 0.23529412 0.46666667
0.30275229 0.73684211 0.72093023 0.453125 0.5 0.59090909
0.66242038 0.53191489 0.80555556 0.078125 0.67782427 0.93396226
0.75815217 0.4673913 0.39795918 0.86238532 0.57480315 0.17073171
0.42307692 0.60326087 0.59174312 0.38181818 0.31192661 0.40789474
0.4953271 0.45 0.88491049 0.80645161 0.95 0.94444444
0.85 0.77333333 0.50980392 0.81410256 0.73023256 0.81021898]
Accuracy: top 1: 61.57% top 5: 86.67%