# Conflicts: # config/measure.py # results/compression_results_auto_small.csv
4.5 KiB
4.5 KiB
| 1 | epoch | train_loss | validation_loss |
|---|---|---|---|
| 2 | 0 | 0.038203152874822226 | 0.01007468316769641 |
| 3 | 1 | 0.009196429502379571 | 0.009720077379471174 |
| 4 | 2 | 0.009038673793042106 | 0.009610504748450897 |
| 5 | 3 | 0.008964756633041698 | 0.009585858197172514 |
| 6 | 4 | 0.008931140641716318 | 0.009600867644226204 |
| 7 | 5 | 0.008908828266692703 | 0.009499007929758286 |
| 8 | 6 | 0.008892161440486582 | 0.009605455486842674 |
| 9 | 7 | 0.008881174305433287 | 0.009481449746976038 |
| 10 | 8 | 0.008872183699634115 | 0.00970931930587289 |
| 11 | 9 | 0.008862181415106961 | 0.009491446118867439 |
| 12 | 10 | 0.008857073408019583 | 0.00946729406493375 |
| 13 | 11 | 0.00884895800594745 | 0.009459692502756578 |
| 14 | 12 | 0.008843754392965792 | 0.009651625354576051 |
| 15 | 13 | 0.008834908272927497 | 0.009442398080368388 |
| 16 | 14 | 0.008829755305629884 | 0.009455852515019967 |
| 17 | 15 | 0.008822814867011307 | 0.00943187994177911 |
| 18 | 16 | 0.008816519091051472 | 0.009423514968925262 |
| 19 | 17 | 0.008811140550923729 | 0.009409872783279505 |
| 20 | 18 | 0.008807593761157645 | 0.009461800281135265 |
| 21 | 19 | 0.00880149622063676 | 0.009408896720496107 |
| 22 | 20 | 0.008796358785390547 | 0.009524200108775136 |
| 23 | 21 | 0.008792251497379177 | 0.009414833995683339 |
| 24 | 22 | 0.00878798051245826 | 0.009416807269261062 |
| 25 | 23 | 0.008784344805015812 | 0.009442471202739599 |
| 26 | 24 | 0.00878047104143189 | 0.009399646851426679 |
| 27 | 25 | 0.008776520166932707 | 0.009409920234378616 |
| 28 | 26 | 0.008774053946049307 | 0.009446325362838268 |
| 29 | 27 | 0.00877281400214814 | 0.009413417439428579 |
| 30 | 28 | 0.008770661085498658 | 0.00940495682060205 |
| 31 | 29 | 0.008768465087984649 | 0.009417549809683429 |
| 32 | 30 | 0.00876514934598888 | 0.00943658693556661 |
| 33 | 31 | 0.008765314949249287 | 0.009398975269441103 |
| 34 | 32 | 0.008762151269915164 | 0.009399307003547117 |
| 35 | 33 | 0.008760039011483393 | 0.009452845440224771 |
| 36 | 34 | 0.008756191631049225 | 0.009397475004686786 |
| 37 | 35 | 0.008754257956830283 | 0.009427362315964301 |
| 38 | 36 | 0.008751021439791612 | 0.009391860575037245 |
| 39 | 37 | 0.008747478588869761 | 0.009389143064190244 |
| 40 | 38 | 0.008744154916418868 | 0.00942032597852075 |
| 41 | 39 | 0.008739684433567926 | 0.00941007169552581 |
| 42 | 40 | 0.008735943676598969 | 0.009400519716751635 |
| 43 | 41 | 0.00873263615571909 | 0.009393544822708799 |
| 44 | 42 | 0.008729347126264919 | 0.009397757453929524 |
| 45 | 43 | 0.008725701429401813 | 0.009392059399927488 |
| 46 | 44 | 0.008723140297296256 | 0.00938395708178956 |
| 47 | 45 | 0.008720736896980929 | 0.009388783796523536 |
| 48 | 46 | 0.008719008777664392 | 0.009381196457695837 |
| 49 | 47 | 0.008716061240497753 | 0.009385784782018586 |
| 50 | 48 | 0.008715456250723834 | 0.009407760416390017 |
| 51 | 49 | 0.008714643922641175 | 0.009384493527871202 |
| 52 | 50 | 0.008712215287250583 | 0.00942497688686478 |
| 53 | 51 | 0.008710978749197138 | 0.009428878775819178 |
| 54 | 52 | 0.00870935251447381 | 0.009377935526544545 |
| 55 | 53 | 0.008708426419351333 | 0.009380641071393995 |
| 56 | 54 | 0.008707099710724387 | 0.009375174062762974 |
| 57 | 55 | 0.008705874277475635 | 0.00937601119625007 |
| 58 | 56 | 0.008703348096971781 | 0.009441648251954666 |
| 59 | 57 | 0.008702214614504884 | 0.009377026935086612 |
| 60 | 58 | 0.008701767129820012 | 0.009402419591984307 |
| 61 | 59 | 0.008701079916805939 | 0.009375535802071368 |
| 62 | 60 | 0.008698968395863677 | 0.009374463488597417 |
| 63 | 61 | 0.008698505843545031 | 0.00937548439178165 |
| 64 | 62 | 0.008697372851612595 | 0.00941963623039664 |
| 65 | 63 | 0.008697200583586116 | 0.009380990598681646 |
| 66 | 64 | 0.008695720268917283 | 0.009369216425056252 |
| 67 | 65 | 0.008696229264597795 | 0.009368591887340133 |
| 68 | 66 | 0.008694589159350867 | 0.009369973812443397 |
| 69 | 67 | 0.008693225543380341 | 0.009370337703206775 |
| 70 | 68 | 0.008692150223980318 | 0.00936367953300282 |
| 71 | 69 | 0.008693366872202868 | 0.00936330371474987 |
| 72 | 70 | 0.008691564555152347 | 0.00936036995664855 |
| 73 | 71 | 0.008690695162153298 | 0.009372037099488936 |
| 74 | 72 | 0.008691385982487776 | 0.00937000487804139 |
| 75 | 73 | 0.008689785334972742 | 0.009358567529062741 |
| 76 | 74 | 0.008687963777458745 | 0.009372979487758844 |
| 77 | 75 | 0.008689111697024536 | 0.009372391138627988 |
| 78 | 76 | 0.008686511684777638 | 0.009357767809641648 |
| 79 | 77 | 0.008686619475149883 | 0.009357165872542955 |
| 80 | 78 | 0.008683587471005436 | 0.009359398888492498 |
| 81 | 79 | 0.008681515429292595 | 0.00936776743438751 |
| 82 | 80 | 0.008677653344017615 | 0.009354117914041645 |
| 83 | 81 | 0.008677359347227067 | 0.009357148641292548 |
| 84 | 82 | 0.00867522060455387 | 0.009371761224413744 |
| 85 | 83 | 0.00867580243278663 | 0.009434228447432792 |
| 86 | 84 | 0.008673858540491526 | 0.009348402056517864 |
| 87 | 85 | 0.008673532580610724 | 0.00936041291515025 |
| 88 | 86 | 0.008671556020248645 | 0.009351397002726268 |
| 89 | 87 | 0.00866867286319788 | 0.009348211624227453 |
| 90 | 88 | 0.008667292430121359 | 0.00933890644379622 |
| 91 | 89 | 0.008661972987403378 | 0.009339850379516346 |
| 92 | 90 | 0.008662919929263156 | 0.009342687033333604 |
| 93 | 91 | 0.008659334642224892 | 0.009429922660065395 |
| 94 | 92 | 0.00865797477268686 | 0.009337762765055822 |
| 95 | 93 | 0.00865722008338017 | 0.009347385051553274 |
| 96 | 94 | 0.008655773483405798 | 0.009332227472866248 |
| 97 | 95 | 0.008655836221537077 | 0.009333810713042321 |
| 98 | 96 | 0.008654475470778142 | 0.00932610999282227 |
| 99 | 97 | 0.008654767870711136 | 0.009346529973705069 |
| 100 | 98 | 0.008652324996318687 | 0.009334174322840083 |
| 101 | 99 | 0.008652484059356542 | 0.009329616149550855 |