Open wanmeihuali opened 9 months ago
Running experiment on sagemaker with git sha 8c4377b94c67b336d765e3bbf4d8bc6b9ad53787
Training job main-backup-8c4377b-231025-180755-tat-train-baseline created
Running experiment on sagemaker with git sha 8c4377b94c67b336d765e3bbf4d8bc6b9ad53787
Training job main-backup-8c4377b-231025-180757-stump created
Running experiment on sagemaker with git sha 8c4377b94c67b336d765e3bbf4d8bc6b9ad53787
Training job main-backup-8c4377b-231025-180805-tat-truck-baseline created
Running experiment on sagemaker with git sha 8c4377b94c67b336d765e3bbf4d8bc6b9ad53787
Training job main-backup-8c4377b-231025-180830-bicycle created
Running experiment on sagemaker with git sha 8c4377b94c67b336d765e3bbf4d8bc6b9ad53787
Training job main-backup-8c4377b-231025-180837-garden created
Training job main-backup-8c4377b-231025-180757-stump final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.025597745552659035 | 0.05397782102227211 | 420490.0 | 28.75018882751465 | 0.8325018882751465 | 0.16749811172485352 | 0.08538329601287842 | 25.29595184326172 | 0.7231685519218445 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
23.00249481201172 | 0.5833531618118286 | 26.34014892578125 | 0.6835675239562988 | 28.75018882751465 | 0.8325018882751465 | 23.69083023071289 | 0.6132415533065796 | 24.234760284423828 | 0.6519967913627625 | 25.29595184326172 | 0.7231685519218445 |
Training job main-backup-8c4377b-231025-180805-tat-truck-baseline final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.027981584891676903 | 0.0447632372379303 | 479960.0 | 25.963247299194336 | 0.8881101608276367 | 0.11188983917236328 | 0.054274316877126694 | 25.06778335571289 | 0.8641229271888733 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
20.45648956298828 | 0.7760704755783081 | 26.511194229125977 | 0.8780505061149597 | 25.963247299194336 | 0.8881101608276367 | 23.210102081298828 | 0.8145042657852173 | 23.79913902282715 | 0.8374910354614258 | 25.06778335571289 | 0.8641229271888733 |
Training job main-backup-8c4377b-231025-180830-bicycle final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.046106982976198196 | 0.09485353529453278 | 594369.0 | 22.38416290283203 | 0.7101602554321289 | 0.2898397445678711 | 0.0914720818400383 | 24.46256446838379 | 0.7122796773910522 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
18.37517738342285 | 0.607547402381897 | 21.774311065673828 | 0.5843327045440674 | 22.38416290283203 | 0.7101602554321289 | 22.4510555267334 | 0.5746819376945496 | 23.22313117980957 | 0.6223793029785156 | 24.46256446838379 | 0.7122796773910522 |
Training job main-backup-8c4377b-231025-180755-tat-train-baseline final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.04494612291455269 | 0.05978633463382721 | 725426.0 | 24.28053092956543 | 0.8808528184890747 | 0.11914718151092529 | 0.10024861246347427 | 20.970958709716797 | 0.8000807166099548 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
16.982261657714844 | 0.7414426803588867 | 22.108158111572266 | 0.7882177829742432 | 24.28053092956543 | 0.8808528184890747 | 19.208932876586914 | 0.7333459258079529 | 19.741897583007812 | 0.7601731419563293 | 20.970958709716797 | 0.8000807166099548 |
Training job main-backup-8c4377b-231025-180837-garden final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.024172671139240265 | 0.04834812134504318 | 512431.0 | 28.663331985473633 | 0.8549500703811646 | 0.14504992961883545 | 0.0685294046998024 | 26.08850860595703 | 0.7925968170166016 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
26.05938148498535 | 0.7589041590690613 | 25.472145080566406 | 0.723265528678894 | 28.663331985473633 | 0.8549500703811646 | 24.430517196655273 | 0.7098124623298645 | 24.98680305480957 | 0.73891282081604 | 26.08850860595703 | 0.7925968170166016 |
Running experiment on sagemaker with git sha 53baabfbbb94fdd65e036169940034f7dba89d1e
Training job main-backup-53baabf-231026-072826-tat-truck-baseline created
Running experiment on sagemaker with git sha 53baabfbbb94fdd65e036169940034f7dba89d1e
Training job main-backup-53baabf-231026-072847-tat-train-baseline created
Running experiment on sagemaker with git sha 53baabfbbb94fdd65e036169940034f7dba89d1e
Training job main-backup-53baabf-231026-072953-stump created
Running experiment on sagemaker with git sha 53baabfbbb94fdd65e036169940034f7dba89d1e
Training job main-backup-53baabf-231026-072957-garden created
Running experiment on sagemaker with git sha 53baabfbbb94fdd65e036169940034f7dba89d1e
Training job main-backup-53baabf-231026-073004-bicycle created
Training job main-backup-53baabf-231026-072953-stump final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.032938938587903976 | 0.07367676496505737 | 420490.0 | 25.097618103027344 | 0.7633719444274902 | 0.23662805557250977 | 0.08446314185857773 | 25.4156494140625 | 0.7253072261810303 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
19.10781478881836 | 0.5994831919670105 | 17.509611129760742 | 0.5462585687637329 | 25.097618103027344 | 0.7633719444274902 | 23.639041900634766 | 0.6120127439498901 | 24.182287216186523 | 0.6502344012260437 | 25.4156494140625 | 0.7253072261810303 |
Training job main-backup-53baabf-231026-072826-tat-truck-baseline final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.02399287559092045 | 0.040774233639240265 | 483455.0 | 26.739599227905273 | 0.8921003341674805 | 0.10789966583251953 | 0.05443387106060982 | 25.070785522460938 | 0.8638872504234314 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
22.244583129882812 | 0.7916557192802429 | 25.099933624267578 | 0.8515645861625671 | 26.739599227905273 | 0.8921003341674805 | 23.073352813720703 | 0.8145865797996521 | 23.86876678466797 | 0.837430477142334 | 25.070785522460938 | 0.8638872504234314 |
Training job main-backup-53baabf-231026-073004-bicycle final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.05437092483043671 | 0.11048278212547302 | 592251.0 | 19.043943405151367 | 0.6650698184967041 | 0.3349301815032959 | 0.09072164446115494 | 24.509775161743164 | 0.7157496809959412 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
23.742084503173828 | 0.6225188970565796 | 17.530200958251953 | 0.5768848657608032 | 19.043943405151367 | 0.6650698184967041 | 22.153194427490234 | 0.5635014176368713 | 23.152196884155273 | 0.6190823912620544 | 24.509775161743164 | 0.7157496809959412 |
Training job main-backup-53baabf-231026-072847-tat-train-baseline final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.03084385395050049 | 0.052931416779756546 | 719205.0 | 26.773529052734375 | 0.8587183356285095 | 0.14128166437149048 | 0.09983851760625839 | 20.88913917541504 | 0.7995631694793701 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
19.78074836730957 | 0.6186875104904175 | 19.806577682495117 | 0.7993912696838379 | 26.773529052734375 | 0.8587183356285095 | 19.227096557617188 | 0.7339518070220947 | 19.68817710876465 | 0.7588903307914734 | 20.88913917541504 | 0.7995631694793701 |
Training job main-backup-53baabf-231026-072957-garden final metrics:
train:iteration | train:l1loss | train:loss | train:num_valid_points | train:psnr | train:ssim | train:ssimloss | val:loss | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.040540724992752075 | 0.08665783703327179 | 503685.0 | 23.79258918762207 | 0.7288737297058105 | 0.27112627029418945 | 0.06857490539550781 | 26.05785369873047 | 0.7927006483078003 |
train:5kpsnr | train:5kssim | train:7kpsnr | train:7kssim | train:psnr | train:ssim | val:5kpsnr | val:5kssim | val:7kpsnr | val:7kssim | val:psnr | val:ssim |
---|---|---|---|---|---|---|---|---|---|---|---|
25.455657958984375 | 0.7257070541381836 | 26.67892074584961 | 0.781999945640564 | 23.79258918762207 | 0.7288737297058105 | 24.33657455444336 | 0.7076260447502136 | 25.031002044677734 | 0.7395359873771667 | 26.05785369873047 | 0.7927006483078003 |
See https://github.com/wanmeihuali/taichi_3d_gaussian_splatting/issues/151