segmentation_test
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: 0.1208
- Mean Iou: 0.8483
- Mean Accuracy: 0.8963
- Overall Accuracy: 0.9648
- Per Category Iou: [0.896665866220625, 0.9313625624392157, 0.6184457649558176, 0.946788356429534]
- Per Category Accuracy: [0.9488350594956452, 0.9690753342283529, 0.6948783145659281, 0.9725778146880949]
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
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
---|---|---|---|---|---|---|---|---|
1.0467 | 0.12 | 20 | 0.9970 | 0.4693 | 0.5892 | 0.8499 | [0.016665768511477424, 0.7530905304669141, 0.32197766779593034, 0.785573865597306] | [0.018291186933739902, 0.9736110066215201, 0.5554138836791528, 0.8094802372221535] |
0.7279 | 0.25 | 40 | 0.5469 | 0.4852 | 0.5502 | 0.8940 | [0.01804951884861912, 0.8184740635118999, 0.24534751963740423, 0.8590701787560616] | [0.018703012459912727, 0.9597806760541293, 0.3156729455312819, 0.9066840327022103] |
0.7806 | 0.38 | 60 | 0.4260 | 0.5242 | 0.6073 | 0.9049 | [0.01807194500339603, 0.8366012049171444, 0.3657984221980414, 0.8765049443865006] | [0.018709584143841017, 0.9630852108788323, 0.5316352476333795, 0.9157347069923247] |
0.5022 | 0.5 | 80 | 0.3776 | 0.5673 | 0.6442 | 0.9155 | [0.13278193831665586, 0.8571556379842626, 0.39241878205971326, 0.8868105485330777] | [0.13725838108756988, 0.9454001415642639, 0.5529329784947034, 0.9412691031815928] |
0.4512 | 0.62 | 100 | 0.3027 | 0.6147 | 0.6726 | 0.9272 | [0.23169125963788326, 0.8698512434242224, 0.4538044468559813, 0.9035720315308671] | [0.2351282792702802, 0.939292533650652, 0.5538645534494219, 0.9621157857635089] |
0.5998 | 0.75 | 120 | 0.2814 | 0.6595 | 0.7168 | 0.9328 | [0.3932326160264655, 0.873639653244202, 0.45899785777309354, 0.9119874363843206] | [0.40385626412912046, 0.9319378939772671, 0.5617421687163787, 0.9697880271073833] |
0.6628 | 0.88 | 140 | 0.2398 | 0.6224 | 0.6878 | 0.9322 | [0.23667963537424397, 0.8731766506602201, 0.4613980137799232, 0.9182017221798935] | [0.23933415698438568, 0.9457139193910193, 0.6013402818446667, 0.9646299239546201] |
0.2891 | 1.0 | 160 | 0.2509 | 0.6993 | 0.8005 | 0.9365 | [0.5407886628522588, 0.8871068137852166, 0.4540803897685749, 0.9151364246964913] | [0.6209277465257698, 0.962521364442151, 0.6770795495822739, 0.9413993019486105] |
0.3733 | 1.12 | 180 | 0.2347 | 0.7473 | 0.8210 | 0.9448 | [0.6897757129718597, 0.8989510444856402, 0.478662489496792, 0.9219419098227718] | [0.7343878695476929, 0.9509685390377233, 0.6376642920153895, 0.9610472258827709] |
0.6024 | 1.25 | 200 | 0.2099 | 0.7563 | 0.8150 | 0.9486 | [0.7054491243993367, 0.9058582674210225, 0.4870865705869561, 0.9266736934314719] | [0.7287186968788882, 0.9590880866678464, 0.6088175916934154, 0.9633364922034189] |
0.3624 | 1.38 | 220 | 0.2075 | 0.7570 | 0.8244 | 0.9477 | [0.6637631174949002, 0.8996125590304884, 0.5362553031346449, 0.9285364229598405] | [0.6913981038501306, 0.971192970317068, 0.6830841308553933, 0.9520221263504635] |
0.6915 | 1.5 | 240 | 0.1703 | 0.7974 | 0.8482 | 0.9540 | [0.8079702418058335, 0.9109995197988137, 0.5379447825240211, 0.9325512132433632] | [0.8631205860189615, 0.9445488751680811, 0.6074684141727886, 0.977596233163672] |
0.3712 | 1.62 | 260 | 0.1817 | 0.7999 | 0.8580 | 0.9529 | [0.8010650098967221, 0.9085553502562573, 0.560168977421881, 0.9298580626286841] | [0.8874336259923242, 0.9404067164614021, 0.6274738009987867, 0.9766288563247306] |
0.2538 | 1.75 | 280 | 0.1751 | 0.8150 | 0.8836 | 0.9566 | [0.8004213101386246, 0.9180591806306987, 0.6065608191143141, 0.9348731824073968] | [0.8772891365683543, 0.9692263290457869, 0.7281184904037895, 0.9597196634547871] |
0.2284 | 1.88 | 300 | 0.1840 | 0.8126 | 0.9042 | 0.9567 | [0.8009792424281661, 0.9194293484770127, 0.5939762508191415, 0.9359433726281363] | [0.9485721921385136, 0.9659392778315237, 0.7435920245322974, 0.9586582645062351] |
0.256 | 2.0 | 320 | 0.1616 | 0.8176 | 0.8884 | 0.9579 | [0.809949528422126, 0.9207851938667173, 0.6025298091308882, 0.937268997247811] | [0.8700449503180695, 0.9619340740732891, 0.7553170196520308, 0.9663523606431447] |
0.4148 | 2.12 | 340 | 0.1642 | 0.8206 | 0.8719 | 0.9582 | [0.7932048029906043, 0.9191135080588984, 0.6322722187829223, 0.937770246889229] | [0.8329324606137076, 0.9742867746553344, 0.7192549377179132, 0.9612368510870202] |
0.2985 | 2.25 | 360 | 0.1486 | 0.8375 | 0.8977 | 0.9613 | [0.8586827106799612, 0.9252188318786676, 0.6245207917181071, 0.9415713272802116] | [0.9194727757040464, 0.969478781784409, 0.7362456788018513, 0.9657594912576178] |
0.1704 | 2.38 | 380 | 0.1467 | 0.8290 | 0.9022 | 0.9601 | [0.8357054588123389, 0.9237357509430961, 0.6162257083130753, 0.9403938047508744] | [0.9392075425407006, 0.9538586328240481, 0.742260144159371, 0.9735591413949309] |
0.1934 | 2.5 | 400 | 0.1474 | 0.8291 | 0.8797 | 0.9599 | [0.8571529421535651, 0.9213274361346364, 0.5977020515839274, 0.9403603679518928] | [0.9043119008814818, 0.9737894189189619, 0.6774254925362808, 0.9630940434994081] |
0.1912 | 2.62 | 420 | 0.1433 | 0.8310 | 0.9069 | 0.9606 | [0.8355815564504465, 0.9245037970991156, 0.6227678339008111, 0.9410534282338662] | [0.9617834673956854, 0.9520821920420963, 0.7389588599697052, 0.9748254174032972] |
0.1921 | 2.75 | 440 | 0.1339 | 0.8286 | 0.8766 | 0.9608 | [0.8511074855171785, 0.9240321564072764, 0.5977901602255353, 0.941451956991874] | [0.9004806091512889, 0.9682032729318744, 0.6685767659770047, 0.9691355452863861] |
0.139 | 2.88 | 460 | 0.1375 | 0.8324 | 0.8971 | 0.9615 | [0.8342633614251669, 0.9255032673803006, 0.6270579504122933, 0.9426635896658996] | [0.9409074181168182, 0.9556867297277537, 0.7161216829630508, 0.9756464136284629] |
0.1557 | 3.0 | 480 | 0.1368 | 0.8347 | 0.8932 | 0.9603 | [0.8546089056727355, 0.9225367596519559, 0.6212372144507865, 0.9405009897594654] | [0.9146294446488968, 0.9608790971251646, 0.7266902402079611, 0.9707082533928404] |
0.2095 | 3.12 | 500 | 0.1299 | 0.8431 | 0.9034 | 0.9629 | [0.8774828339164978, 0.9283559261158525, 0.6227224847390085, 0.9439444287208694] | [0.9498317648914358, 0.9668135908051043, 0.727485909002177, 0.9695951469339585] |
0.1639 | 3.25 | 520 | 0.1300 | 0.8384 | 0.8794 | 0.9628 | [0.8790845930676439, 0.9277390439822828, 0.6029040896735798, 0.9440283579425929] | [0.9080161400557278, 0.9708537617842183, 0.6681270401367957, 0.9706067913536859] |
0.1139 | 3.38 | 540 | 0.1235 | 0.8355 | 0.8815 | 0.9632 | [0.8830324246537594, 0.928376002336871, 0.5856632431257472, 0.9450535716038398] | [0.9476412035820059, 0.9631465359669655, 0.639146904675419, 0.9760456588476107] |
0.2574 | 3.5 | 560 | 0.1264 | 0.8453 | 0.9043 | 0.9638 | [0.878600355282667, 0.9295598939555374, 0.6275502561490758, 0.945452356561073] | [0.9566728878607854, 0.9609682370480884, 0.7246467057582204, 0.9750175535837675] |
0.2927 | 3.62 | 580 | 0.1309 | 0.8446 | 0.8981 | 0.9633 | [0.8866855291248271, 0.9282894217693001, 0.6190576519555571, 0.944518781436582] | [0.9452994935422253, 0.9598107425660218, 0.7115206416747593, 0.9759016962109369] |
0.4659 | 3.75 | 600 | 0.1202 | 0.8484 | 0.9041 | 0.9641 | [0.8833081778126276, 0.9297489957164383, 0.6347412766855173, 0.9456458562459887] | [0.9525152024954875, 0.9567847534440064, 0.7285978684971991, 0.9785108795019711] |
0.1478 | 3.88 | 620 | 0.1207 | 0.8503 | 0.9115 | 0.9644 | [0.8839341322345905, 0.930666904641919, 0.640631018371209, 0.9461269754236669] | [0.9544604209382612, 0.9586230491204685, 0.7562115292902486, 0.9766407602120007] |
0.2361 | 4.0 | 640 | 0.1206 | 0.8509 | 0.9104 | 0.9639 | [0.8843630597662286, 0.9290525728561428, 0.6450059707401802, 0.9453487498415234] | [0.9602916951439637, 0.9520253703081671, 0.7487638716947004, 0.9805396552894644] |
0.22 | 4.12 | 660 | 0.1193 | 0.8448 | 0.8875 | 0.9643 | [0.8981674375904806, 0.9304938750380576, 0.6046215297860035, 0.9459224283816728] | [0.9472622364754745, 0.9670648514793784, 0.6612946667951598, 0.9744785306883144] |
0.209 | 4.25 | 680 | 0.1181 | 0.8503 | 0.9019 | 0.9645 | [0.8927503260337429, 0.9310490279930463, 0.6313541481285349, 0.9459033573690366] | [0.9507189422217549, 0.9618490401497869, 0.7188299220887047, 0.9762163122315232] |
0.2477 | 4.38 | 700 | 0.1210 | 0.8483 | 0.8967 | 0.9646 | [0.8965441720351905, 0.9309945711672964, 0.619250454020142, 0.9463799993792809] | [0.9505327445104533, 0.9683300291075624, 0.6951229456548329, 0.9726875536488669] |
0.2449 | 4.5 | 720 | 0.1218 | 0.8479 | 0.8985 | 0.9641 | [0.8961950935913541, 0.9301026110955253, 0.6193945084735495, 0.9457735746871611] | [0.9454922629374551, 0.9726557657238586, 0.7074187466486777, 0.9685915004384908] |
0.1402 | 4.62 | 740 | 0.1205 | 0.8513 | 0.9089 | 0.9646 | [0.8883404276098935, 0.9311559198709245, 0.6392782798591807, 0.9462383840511697] | [0.9563946865744879, 0.9610148600092611, 0.7421637743364691, 0.9758302728873157] |
0.1993 | 4.75 | 760 | 0.1156 | 0.8513 | 0.9002 | 0.9650 | [0.8973513861058572, 0.9315816840805964, 0.6294303742460324, 0.9468717796656311] | [0.9446992797434415, 0.9648566185002029, 0.7158152763466448, 0.9752565613203643] |
0.1458 | 4.88 | 780 | 0.1162 | 0.8539 | 0.9091 | 0.9651 | [0.8940502189002697, 0.932053937919347, 0.6428052076917813, 0.9468840079361927] | [0.9550781592275205, 0.9630270646289607, 0.7427543483793808, 0.9753759721895434] |
0.0971 | 5.0 | 800 | 0.1208 | 0.8483 | 0.8963 | 0.9648 | [0.896665866220625, 0.9313625624392157, 0.6184457649558176, 0.946788356429534] | [0.9488350594956452, 0.9690753342283529, 0.6948783145659281, 0.9725778146880949] |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2
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