CoolFace
Modelpublic

Caraaaaa/image_segmentation_text

sourceHugging Faceotherupdated 3y agoView on Hugging Face
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Model Card

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imagesegmentationtext_v2

This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0615
  • Mean Iou: 0.8781
  • Mean Accuracy: 0.9110
  • Overall Accuracy: 0.9734
  • Per Category Iou: [0.9705763603242805, 0.7855978863350824]
  • Per Category Accuracy: [0.9925963343496583, 0.8293473752101665]

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 6e-05
  • trainbatchsize: 2
  • evalbatchsize: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 50

Training results

Training LossEpochStepValidation LossMean IouMean AccuracyOverall AccuracyPer Category IouPer Category Accuracy
0.51720.4200.59840.62010.83120.8580[0.8433386612833417, 0.39680175287609587][0.866190330235608, 0.7961823484817947]
0.47670.8400.40350.52580.58530.8882[0.8856626480452995, 0.1659390336502284][0.9810900280003672, 0.18954193123051938]
0.34391.2600.34740.69950.85730.9074[0.8979547121624778, 0.5009503846168084][0.9228071003413048, 0.7918197268517736]
0.28421.6800.28280.69230.77220.9230[0.9174404161237479, 0.4671543716020125][0.9692542242141893, 0.5751911816528029]
0.29412.01000.24120.72740.82260.9294[0.9232295355579201, 0.5316079622856148][0.9621363189327741, 0.6830129526301212]
0.21592.41200.23870.74710.88770.9274[0.9195102054074465, 0.5746316429439954][0.9395897739623381, 0.8357430695431796]
0.20132.81400.20590.76600.89940.9345[0.9272560031451658, 0.6047195723903955][0.9453276278068868, 0.8534035600552902]
0.18223.21600.15980.80160.86690.9533[0.9487517424447746, 0.6545065297960031][0.9797635674372861, 0.7541327875396765]
0.12613.61800.15330.78700.85530.9494[0.9446523952139291, 0.6294161895000621][0.9782770257479946, 0.7322611643453532]
0.17514.02000.14340.80600.86090.9556[0.9513646199038472, 0.6606627045566984][0.9846122449614638, 0.7371309163585958]
0.15564.42200.13400.81020.86450.9566[0.9524442279212987, 0.6679515135667692][0.984852971709032, 0.7440538962567276]
0.10684.82400.12530.78980.83580.9531[0.9490085335911248, 0.6306787839687829][0.9890518166701155, 0.6826157004965977]
0.12155.22600.10730.84970.90910.9652[0.9614007926531548, 0.7380488065311127][0.9823778512721868, 0.8358783043120386]
0.0915.62800.10770.83250.88190.9622[0.9583632540158915, 0.7067172285496849][0.9867697098157909, 0.7770472788553937]
0.10096.03000.10640.82380.86800.9608[0.9569876540030186, 0.6906903674483074][0.9892049828448698, 0.7467735454785426]
0.09846.43200.10600.83110.87610.9623[0.9585729019064059, 0.7037087870923661][0.9887282833788597, 0.7633723130216779]
0.08136.83400.09870.84190.88830.9645[0.9608922897234371, 0.722840581644497][0.9878806832041188, 0.7887346836871759]
0.06257.23600.09020.84750.88910.9662[0.9627445497647863, 0.7323412821849365][0.9898383923982556, 0.7883172763717552]
0.07347.63800.09270.84690.89590.9654[0.961803716924761, 0.7319708674782419][0.9867425686313254, 0.8049635061174228]
0.07338.04000.08760.87110.93070.9701[0.9666965487625444, 0.7754727726647843][0.9822345389032576, 0.8790988163056722]
0.05848.44200.09180.86070.91210.9683[0.964859785245781, 0.7564785981949649][0.9855508631847466, 0.838696128774708]
0.06398.84400.08580.87350.93490.9706[0.967139403611975, 0.7798182886949773][0.9814883292042429, 0.8884020581691553]
0.08599.24600.08630.84420.87900.9661[0.9627025051107989, 0.7256751249820441][0.9927421533884905, 0.765291606472024]
0.06769.64800.07960.86920.92250.9701[0.9667776147303454, 0.7716995072886178][0.9847239214274811, 0.8603714014873224]
0.085610.05000.07890.87210.92310.9709[0.9676681841843127, 0.7764766898351453][0.9856164687866871, 0.8604845305728103]
0.073210.45200.07960.86110.90520.9690[0.9656431512846645, 0.7564856330988124][0.9885161672429414, 0.8218307926968024]
0.064210.85400.08810.83780.87180.9648[0.9613570133699026, 0.7141516019397048][0.9932708878642084, 0.7502987518090901]
0.080611.25600.07920.86050.90390.9689[0.9655732989225007, 0.7554214468864908][0.9888003717477902, 0.8190597802695073]
0.064211.65800.07680.86630.90760.9703[0.9671300467068968, 0.7654769403248215][0.9895412223594264, 0.8256966866181296]
0.050312.06000.07960.86370.90560.9697[0.9664822125443101, 0.7610012493038518][0.9893804497380703, 0.8217891819986919]
0.071112.46200.07990.85240.88760.9678[0.9645090425676253, 0.7402596444414385][0.9923599294467503, 0.7828006080363261]
0.062212.86400.07390.86780.91500.9702[0.9669781140184328, 0.7687031945706295][0.9871926455342293, 0.84275642267627]
0.055113.26600.07150.87410.91780.9719[0.9687595252839901, 0.7794271755462193][0.988435608058477, 0.8472263218873572]
0.071713.66800.07570.85980.89410.9694[0.9662689349888198, 0.7532485600087165][0.9925298643787859, 0.7955731418547709]
0.063514.07000.07180.87320.91740.9716[0.96850746670701, 0.7778616932414459][0.9882812317672178, 0.8464279166173623]
0.052314.47200.06630.88760.93580.9746[0.9716791978883015, 0.8036108039561688][0.9865335642235624, 0.8850107862731508]
0.057714.87400.06760.88330.93660.9733[0.9702350309780267, 0.796362403107551][0.9846131957672891, 0.8885314414335925]
0.043515.27600.07110.86710.90390.9708[0.9677187286152693, 0.7665006963915808][0.9913234646603627, 0.8165254286877156]
0.067315.67800.07170.86370.89640.9704[0.9673187596918544, 0.7601149728604968][0.9930802945146975, 0.7996782972902333]
0.056316.08000.06540.88450.92510.9744[0.971468043944435, 0.7974893910508356][0.989447006145836, 0.860792709805691]
0.058616.48200.06930.87320.91290.9719[0.9688913807063626, 0.7775406555703152][0.9900519779613582, 0.8357222641941243]
0.056416.88400.06980.86980.90450.9715[0.9685318541511667, 0.7711066182518113][0.9921181654564637, 0.8168225550789108]
0.047817.28600.06820.87360.91100.9722[0.9691646685069771, 0.7780200639749164][0.9909173841360986, 0.831173044589764]
0.048517.68800.06460.87900.91920.9732[0.9702169077246766, 0.7878410180791867][0.989739854340005, 0.8486430361245876]
0.056618.09000.06930.86670.90290.9708[0.9676668469869958, 0.7656600486037874][0.991562981291426, 0.8142504938019565]
0.045518.49200.07270.86210.89550.9700[0.9668821926221384, 0.7572945442521496][0.9928309240778092, 0.7981315496214076]
0.045118.89400.07430.86160.89570.9698[0.9667066236459168, 0.75648894444205][0.9925660814370375, 0.7987895187852797]
0.047919.29600.06480.87910.91700.9733[0.9704226039041611, 0.787839253664714][0.9906320559516382, 0.8433539262944503]
0.042919.69800.06430.88140.92170.9737[0.9707538355760997, 0.7919781103864696][0.9896213493594248, 0.8538053633589195]
0.041220.010000.06850.87100.90820.9716[0.9685757534109218, 0.7733473306325775][0.9910794533108528, 0.8252383187717562]
0.051720.410200.07000.86810.90490.9710[0.9679606643038668, 0.768307799914675][0.9913238968448287, 0.8184479729738515]
0.062220.810400.07050.86610.90290.9706[0.967473334999663, 0.7646563357741486][0.9913285644370616, 0.8145313660142023]
0.050121.210600.06590.87350.90920.9723[0.9692782576787035, 0.7776627515629433][0.9915888259224934, 0.826863736666697]
0.033121.610800.06560.87400.90950.9724[0.969431404124596, 0.7786407327387083][0.9916812269613265, 0.8273624148768648]
0.040922.011000.06270.88120.91800.9739[0.9709853246351019, 0.791378914530232][0.991000449990466, 0.8449500866672821]
0.050722.411200.06700.87120.90540.9719[0.96890284080009, 0.7735870738116131][0.992284124291412, 0.8184843823346982]
0.05522.811400.06500.87400.91060.9723[0.969333155377141, 0.7786920795104981][0.9912426461652186, 0.8299858393592993]
0.062123.211600.06080.88510.92410.9746[0.97174575429152, 0.7984980757048741][0.9900816258157266, 0.8580698097480862]
0.047523.611800.06480.87570.90990.9728[0.969923983536794, 0.781504588462575][0.9921419356020943, 0.8276972509632227]
0.071924.012000.05970.88830.92900.9752[0.9723810750370141, 0.8042819715081054][0.9893649775341871, 0.8686207223877259]
0.043224.412200.06710.87450.91110.9724[0.9694436234993048, 0.7795285436234692][0.991234693971044, 0.8309240305682591]
0.048724.812400.06270.87940.91580.9735[0.9705926889014477, 0.7881517515303139][0.9911871536797828, 0.840397616227132]
0.043125.212600.07030.86070.89110.9699[0.9668504181402485, 0.7545441416676626][0.9940878893787556, 0.7880988202066751]
0.048525.612800.06860.86630.89920.9709[0.9678797771258784, 0.7647121997104036][0.992901802330235, 0.8055415047208637]
0.040126.013000.06450.87410.90940.9724[0.9694702128324741, 0.7787894408819918][0.9917601438448201, 0.827058136646932]
0.035826.413200.06500.87520.90800.9728[0.9699118666008384, 0.7804262038251969][0.9926968604564524, 0.823297569805197]
0.037126.813400.06240.87940.91380.9736[0.9707671601979381, 0.7880723266892008][0.9919919675923885, 0.8355421678913648]
0.037327.213600.05930.89050.93030.9757[0.972963140756407, 0.808064312770677][0.9896636170002007, 0.8708904559362212]
0.045927.613800.06500.87480.90740.9727[0.9698368752489902, 0.7797103933881729][0.9927813957380043, 0.8220466481932505]
0.044828.014000.05850.89130.92940.9760[0.9732524861024707, 0.8092622781494344][0.9902627975438784, 0.8685342501557151]
0.046628.414200.05910.88680.92270.9751[0.9723752980279239, 0.8013039527210407][0.9912211233788112, 0.8542169191699186]
0.04628.814400.06240.87820.91290.9734[0.9704629995935647, 0.7859491844731833][0.9919060493205455, 0.8337990697408304]
0.04429.214600.06460.87380.90790.9724[0.9694836939653589, 0.7780494172207805][0.9922285453690829, 0.8235309798149104]
0.028829.614800.06390.87450.90870.9726[0.9696471298812925, 0.7793704984065971][0.9921753866797636, 0.8252409194403881]
0.061330.015000.05990.88390.92190.9744[0.9715329244431512, 0.7962728238571309][0.9904880520875633, 0.853244269101586]
0.04430.415200.06280.87570.90970.9729[0.9699453251794836, 0.7814895244296873][0.9922406465341312, 0.8271010476793583]
0.029330.815400.06170.87800.91250.9733[0.9704425104125867, 0.7856417917220885][0.9919949928836506, 0.8329473507638814]
0.042831.215600.05990.88180.91550.9742[0.9713541972985056, 0.7921493091394499][0.9921727071360743, 0.8387878023439826]
0.064531.615800.06270.87440.90590.9727[0.9698458799171074, 0.7789683055241065][0.9932316455146946, 0.8186261187751371]
0.056732.016000.06330.87490.90900.9727[0.9697435930361873, 0.7800611650843169][0.992193538427336, 0.8258657300792034]
0.028532.416200.06200.87680.91150.9731[0.9701471869845076, 0.783517826129869][0.991947279718603, 0.8309766941080552]
0.057132.816400.06010.88110.91530.9740[0.9711643268487495, 0.7909989321972878][0.9920145276215143, 0.8385108311346847]
0.040133.216600.06420.87340.90600.9725[0.9695272707444462, 0.7772926276022758][0.9928285902816927, 0.8192216718918434]
0.051233.616800.06630.87060.90270.9719[0.9689150151187212, 0.7721857742809729][0.9930920499321729, 0.8123090946682392]
0.037634.017000.06280.87800.91220.9733[0.9704377847240172, 0.7854762211546131][0.9920699336700569, 0.8323290417966459]
0.02834.417200.06420.87370.90780.9724[0.9694875787740898, 0.7780070979332923][0.9922682199030628, 0.8232540086056125]
0.052934.817400.05970.88310.91820.9744[0.971576972958672, 0.7947159780070965][0.9916307478156965, 0.8447452840125196]
0.040535.217600.06330.87550.90790.9729[0.9700091754702059, 0.7809148433321386][0.992833430747712, 0.8230108460885294]
0.058635.617800.06530.87140.90590.9719[0.9689169040586796, 0.7739549474059][0.9921412441069487, 0.8197053962573778]
0.057236.018000.06280.87590.91050.9729[0.9699524292504794, 0.7819443592605768][0.9920137496894754, 0.8289169645515863]
0.050636.418200.05990.88200.91720.9741[0.9712925656410623, 0.7926478079614093][0.9916029151360853, 0.8427128614766857]
0.032636.818400.06640.86920.90080.9716[0.9686386462229684, 0.7696646394310533][0.9933210212622656, 0.8083313719957401]
0.033237.218600.06110.87920.91320.9736[0.9707461298544804, 0.7876790150283312][0.9921293158156869, 0.8343114014613157]
0.060137.618800.06060.88080.91500.9739[0.9711010689625178, 0.7905405861230448][0.9920064025535533, 0.8380732686373666]
0.036838.019000.06400.87320.90500.9725[0.9695594225767187, 0.7769055994221483][0.9931751157865403, 0.8167887463866961]
0.042238.419200.06170.87740.91180.9732[0.9702923463415809, 0.7844662873966847][0.9920254186700578, 0.8315215341864394]
0.043238.819400.06330.87590.91040.9729[0.9699529639553718, 0.7819260584157408][0.992026369475883, 0.8288233404808376]
0.058639.219600.06110.87930.91350.9736[0.9707487378178947, 0.7878378709986136][0.9920483244467564, 0.834959618117818]
0.035239.619800.06470.87410.90700.9726[0.9696673702028153, 0.7785742945526019][0.9927034296603359, 0.8213054576331574]
0.036140.020000.06300.87640.91010.9730[0.9701097833950302, 0.782591672915463][0.9923145500778191, 0.8278324857320817]
0.042140.420200.06100.87860.91170.9735[0.970677588650168, 0.7865422237867158][0.9924901034079128, 0.8309727931051073]
0.045840.820400.06250.87590.90840.9730[0.9701118739649276, 0.7817402653153365][0.9928041286409164, 0.8240530640427653]
0.041441.220600.06190.87810.91170.9734[0.9705327749561811, 0.7857585839593991][0.9923163652525764, 0.831171744255448]
0.0541.620800.06050.88030.91360.9739[0.9710563114216053, 0.7895525940174909][0.9923900094855846, 0.8347476636243178]
0.030642.021000.06010.88160.91690.9740[0.9712027944676178, 0.792013158538375][0.9915832939613285, 0.8421550180551419]
0.052342.421200.06130.87900.91230.9736[0.9707498261404447, 0.7872513405027708][0.9923932940875263, 0.8322952331044311]
0.034742.821400.05910.88310.91800.9744[0.9715892664031848, 0.7947023514847699][0.9916940196215205, 0.8443525830491019]
0.043343.221600.06070.88020.91350.9739[0.9710164270074672, 0.7893017221767921][0.9923620903690803, 0.8346481880491474]
0.040843.621800.05950.88260.91760.9743[0.9714433752474874, 0.7937025271738631][0.9916428489807448, 0.8435957884772175]
0.031844.022000.06260.87720.91070.9732[0.970326566740187, 0.7840985118681589][0.9923819708545168, 0.8290287933027581]
0.04844.422200.05980.88120.91560.9740[0.9711679522425044, 0.7911830955700955][0.9919216943982151, 0.8392585233663575]
0.033244.822400.06120.87850.91110.9736[0.9707002963862882, 0.7863211248436672][0.9927155308253842, 0.8294058902543844]
0.060945.222600.05970.88110.91520.9740[0.9711846631400414, 0.7910596755855982][0.992068291369086, 0.8382553154416]
0.035145.622800.06100.87850.91130.9735[0.9706826467363787, 0.7863583642701348][0.9926178571360657, 0.830022898887304]
0.044446.023000.05920.88250.91680.9743[0.9714948390728185, 0.7935759738110126][0.9919480576506418, 0.8416394354988668]
0.050846.423200.06070.87940.91220.9737[0.9708919841673713, 0.7879353992275995][0.9926144860972308, 0.8317074819936205]
0.03846.823400.06010.88160.91590.9741[0.9712634066834908, 0.7918441714173262][0.9919517744370495, 0.8397806075942125]
0.03547.223600.06060.88000.91340.9738[0.9709804766649791, 0.7890313829990002][0.992362781864226, 0.83435821349669]
0.03347.623800.06070.88000.91340.9738[0.9709604358552277, 0.7889657724192867][0.9923135128351007, 0.8345812208318759]
0.041148.024000.06140.87790.91070.9734[0.9705508928119433, 0.7853294217376947][0.9926405900389779, 0.8288025351317824]
0.037848.424200.05960.88160.91620.9741[0.9712621476572101, 0.7919987894404409][0.9918544464953037, 0.8405243988229374]
0.037648.824400.05960.88160.91600.9741[0.9712701752402172, 0.7919569993962999][0.991914779446759, 0.8401206450178341]
0.040549.224600.05990.88080.91480.9739[0.9711090571855628, 0.7904560916024725][0.9920912835826778, 0.8374790158549763]
0.035749.624800.06010.88050.91420.9739[0.9710507537711823, 0.7898657116838633][0.9921822151943266, 0.8363132661407248]
0.050850.025000.06150.87810.91100.9734[0.9705763603242805, 0.7855978863350824][0.9925963343496583, 0.8293473752101665]

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0