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---
license: other
tags:
- generated_from_trainer
model-index:
- name: segment_test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# segment_test
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1260
- Mean Iou: 0.8447
- Mean Accuracy: 0.9060
- Overall Accuracy: 0.9643
- Per Category Iou: [0.8581731584290526, 0.9316708017224354, 0.6429457606853357, 0.9461543989839276]
- Per Category Accuracy: [0.9425328146084153, 0.9716290009653072, 0.7414471782174548, 0.9684613946705924]
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------:|
| 1.0598 | 0.12 | 20 | 1.0566 | 0.4321 | 0.5515 | 0.8279 | [0.006337257377741027, 0.7300264416674316, 0.23785776348718268, 0.7540601698014678] | [0.008091933477034156, 0.9660296098187956, 0.4518657444815921, 0.779822911077032] |
| 0.7539 | 0.25 | 40 | 0.6128 | 0.4529 | 0.5206 | 0.8749 | [0.00885438037222906, 0.7887343476637405, 0.18630294846181414, 0.827538656414587] | [0.009217881990081138, 0.9747549910409742, 0.23250084632472676, 0.8657848800171862] |
| 0.8122 | 0.38 | 60 | 0.4928 | 0.4920 | 0.5507 | 0.8982 | [0.02270113673871408, 0.8263637783329851, 0.2554015068180403, 0.8635887381305902] | [0.023653681019224364, 0.9630036206967801, 0.30407150146655104, 0.9122355221296055] |
| 0.5643 | 0.5 | 80 | 0.4269 | 0.5063 | 0.5663 | 0.9129 | [0.007592876375505398, 0.8532772644930355, 0.27466317854807065, 0.8898355351518092] | [0.007684489073480188, 0.9441805272844986, 0.3632055074118278, 0.9501073674832299] |
| 0.4774 | 0.62 | 100 | 0.3648 | 0.5490 | 0.6034 | 0.9218 | [0.054267747505144744, 0.8633878614911209, 0.37650159164096025, 0.9020084353341656] | [0.055975413139862956, 0.9428365409577416, 0.45329399467742054, 0.961363980883101] |
| 0.6967 | 0.75 | 120 | 0.3155 | 0.6158 | 0.6710 | 0.9325 | [0.19913477919641662, 0.8733583185910088, 0.47153849968591927, 0.9190236996330312] | [0.20509568371799589, 0.9502280021743253, 0.5638919570734214, 0.9648268960892941] |
| 0.4543 | 0.88 | 140 | 0.2964 | 0.6272 | 0.7016 | 0.9310 | [0.2268179599804783, 0.8694887954672872, 0.4961026114602021, 0.9165896188501754] | [0.2321184480311235, 0.9344494411072529, 0.6716976656263668, 0.9680582434884342] |
| 0.2924 | 1.0 | 160 | 0.2722 | 0.6820 | 0.7592 | 0.9384 | [0.40849985639476094, 0.8843766461027478, 0.5120505100078259, 0.9231923075849184] | [0.4548831992709812, 0.9611082383832005, 0.667739089824088, 0.9532322308907735] |
| 0.3467 | 1.12 | 180 | 0.2517 | 0.6815 | 0.7430 | 0.9414 | [0.40527347045732925, 0.8910632241964158, 0.5029203059015287, 0.9266932255262942] | [0.447198710197501, 0.9557005046935547, 0.6038508392823166, 0.9651288642296557] |
| 0.5212 | 1.25 | 200 | 0.2396 | 0.6752 | 0.7408 | 0.9427 | [0.3668495492266549, 0.8948194469733646, 0.5099936563424119, 0.9292469056689828] | [0.3789189141825701, 0.965308543339751, 0.6575510698285852, 0.9614078764674099] |
| 0.3599 | 1.38 | 220 | 0.2108 | 0.6717 | 0.7162 | 0.9446 | [0.3204229923658836, 0.891874970369172, 0.5386909667961237, 0.9357227289520356] | [0.32437612813907435, 0.9667832593900233, 0.605627503453252, 0.9680877242092517] |
| 0.7198 | 1.5 | 240 | 0.2018 | 0.7692 | 0.8618 | 0.9527 | [0.6678205541462868, 0.9118050318864169, 0.5610132418656683, 0.9363469668607539] | [0.8350594956451641, 0.9497174012785288, 0.6927260551877853, 0.9696466684460499] |
| 0.3682 | 1.62 | 260 | 0.1931 | 0.7812 | 0.8479 | 0.9538 | [0.6890403931363558, 0.9109837638365132, 0.5887742209415688, 0.93605613049878] | [0.7620327532726986, 0.9497927662356516, 0.7058595323345466, 0.9739980042388998] |
| 0.3358 | 1.75 | 280 | 0.1947 | 0.7916 | 0.8837 | 0.9550 | [0.7285153761152414, 0.9167544021441286, 0.5844378827851311, 0.9366799980170186] | [0.8390747945253492, 0.9631461386121828, 0.7712946420849488, 0.9611668227501886] |
| 0.2334 | 1.88 | 300 | 0.2014 | 0.7843 | 0.8673 | 0.9522 | [0.7115100993908304, 0.9111127309647635, 0.5831612483285399, 0.9312333415206432] | [0.850726390130207, 0.9751160540868734, 0.6929311499390893, 0.9502407282203037] |
| 0.2996 | 2.0 | 320 | 0.1701 | 0.8027 | 0.8896 | 0.9568 | [0.7526564111480359, 0.9206156591940219, 0.5997533073741746, 0.9377288799677301] | [0.8344833780207841, 0.964968540097336, 0.7965929561072522, 0.9622910891033862] |
| 0.4622 | 2.12 | 340 | 0.1897 | 0.7614 | 0.8286 | 0.9509 | [0.5700844122547072, 0.9050700733042791, 0.6361100555452245, 0.9344921716585569] | [0.6064108967281776, 0.975059629707727, 0.777640224269875, 0.9551298779200561] |
| 0.338 | 2.25 | 360 | 0.1713 | 0.8093 | 0.8947 | 0.9579 | [0.7434863865211815, 0.9179570569529378, 0.6345544665942896, 0.9411654222120547] | [0.9167652419255911, 0.9513808608505936, 0.7380297560360868, 0.9725677707832107] |
| 0.1828 | 2.38 | 380 | 0.1613 | 0.8102 | 0.8854 | 0.9583 | [0.7563041981028708, 0.923073161283024, 0.6226932638283688, 0.9387242789473116] | [0.8467351874244257, 0.9575329724998702, 0.7662636431252486, 0.9708901596701879] |
| 0.1848 | 2.5 | 400 | 0.1523 | 0.8332 | 0.8882 | 0.9617 | [0.8272877802882616, 0.9256725856927198, 0.6369852470922355, 0.9430524306296677] | [0.8886931987452464, 0.9707900525673887, 0.7260329485953481, 0.9672511041320438] |
| 0.2053 | 2.62 | 420 | 0.1450 | 0.8382 | 0.9129 | 0.9626 | [0.8318187789064231, 0.9285519737454524, 0.6480460535396757, 0.9442850494628351] | [0.9293894467518357, 0.9631609731907377, 0.7888883123172988, 0.970120219961517] |
| 0.1596 | 2.75 | 440 | 0.1376 | 0.8327 | 0.8953 | 0.9624 | [0.8243205167317957, 0.928415735271021, 0.6344793824796972, 0.9436346449664342] | [0.9292602036345793, 0.9591271598881472, 0.717386845766276, 0.9752671632199643] |
| 0.137 | 2.88 | 460 | 0.1472 | 0.8260 | 0.9081 | 0.9616 | [0.7858947726139123, 0.9279875195406946, 0.6464381724674384, 0.9437068326674424] | [0.9422546133221177, 0.9608167124242775, 0.7587838622553998, 0.9706571968763456] |
| 0.1679 | 3.0 | 480 | 0.1471 | 0.8331 | 0.9126 | 0.9624 | [0.8265760388185004, 0.9295336697547381, 0.6321998556258659, 0.9441039056088667] | [0.9403510155442231, 0.9637791247810575, 0.7769013889609604, 0.9693229385117723] |
| 0.1736 | 3.12 | 500 | 0.1322 | 0.8402 | 0.8960 | 0.9634 | [0.8539363341788129, 0.9291877911278092, 0.632669557547822, 0.9451061440414477] | [0.9248133641764366, 0.9646743651065282, 0.721404726074956, 0.9731695680841902] |
| 0.234 | 3.25 | 520 | 0.1355 | 0.8448 | 0.9076 | 0.9632 | [0.8526502893205608, 0.9289085404109714, 0.6534740415947964, 0.944330630190735] | [0.9257553055394915, 0.9662036512136275, 0.7685765188748946, 0.9699754203327694] |
| 0.1183 | 3.38 | 540 | 0.1256 | 0.8402 | 0.8954 | 0.9637 | [0.8579969655846054, 0.9294856863546612, 0.6276158375419669, 0.9457592749372996] | [0.9389994392163048, 0.9661690813475308, 0.7035145333106, 0.9727224283186038] |
| 0.2085 | 3.5 | 560 | 0.1279 | 0.8480 | 0.9079 | 0.9642 | [0.8653295827282605, 0.9310186709909459, 0.6502631789997088, 0.9455883129741319] | [0.9333061703730964, 0.9630336872086728, 0.7613438401150507, 0.9739094690773278] |
| 0.3477 | 3.62 | 580 | 0.1419 | 0.8392 | 0.9182 | 0.9627 | [0.8356838761929862, 0.9295750569194587, 0.6477355195833494, 0.9437915808167578] | [0.9515710705711231, 0.9679427406460035, 0.7873562792352684, 0.9660274217203163] |
| 0.4279 | 3.75 | 600 | 0.1241 | 0.8453 | 0.8990 | 0.9639 | [0.8543157504970579, 0.9297143070002641, 0.6517228913538011, 0.9456141839889123] | [0.9299589926922874, 0.955372819449404, 0.7305771563983385, 0.9801914665868114] |
| 0.1622 | 3.88 | 620 | 0.1255 | 0.8438 | 0.9206 | 0.9638 | [0.8381374979278546, 0.9308920069470188, 0.6604220534808366, 0.9458239210474509] | [0.9524867251984649, 0.95692011897332, 0.7977592780664754, 0.9753784831657644] |
| 0.1982 | 4.0 | 640 | 0.1229 | 0.8484 | 0.9091 | 0.9647 | [0.8568106859830862, 0.9316640237424656, 0.6584440596013207, 0.9466997405108393] | [0.9452293955803235, 0.9595748462766798, 0.754422510013813, 0.9770213126081696] |
| 0.2273 | 4.12 | 660 | 0.1237 | 0.8444 | 0.8986 | 0.9640 | [0.8592317269149002, 0.9306231098333563, 0.6421928363458029, 0.9456102319021257] | [0.9358165536337031, 0.9691394407999653, 0.7183357178686949, 0.970921035377795] |
| 0.2371 | 4.25 | 680 | 0.1216 | 0.8460 | 0.9096 | 0.9645 | [0.8583380957371707, 0.9321090417297068, 0.6472432759450742, 0.9464390728899327] | [0.9508328514098453, 0.961341618092252, 0.7507901089967407, 0.9753970829896241] |
| 0.2474 | 4.38 | 700 | 0.1283 | 0.8411 | 0.9093 | 0.9635 | [0.8497493402399663, 0.9309167522466655, 0.6387399097291454, 0.9448643127623003] | [0.9486861013266039, 0.9710814460747176, 0.7504342819583336, 0.9668204252105732] |
| 0.2696 | 4.5 | 720 | 0.1273 | 0.8430 | 0.9049 | 0.9633 | [0.8574838830140721, 0.929602014003094, 0.6403298755318946, 0.9444960387864841] | [0.9355734013283564, 0.9743545898715855, 0.7448102379346218, 0.9649164542411783] |
| 0.1506 | 4.62 | 740 | 0.1255 | 0.8479 | 0.9182 | 0.9646 | [0.8525455460809918, 0.9327217587877741, 0.6600164613831294, 0.9464177410883513] | [0.9496433766188248, 0.9639090597950073, 0.7866569802639545, 0.972458775815393] |
| 0.2033 | 4.75 | 760 | 0.1209 | 0.8501 | 0.9107 | 0.9650 | [0.8658943552605436, 0.9327154832962604, 0.6546122598692601, 0.9470460950988947] | [0.935571210767047, 0.9689885784341254, 0.76733359526157, 0.9708881136895634] |
| 0.1636 | 4.88 | 780 | 0.1203 | 0.8483 | 0.9157 | 0.9648 | [0.8518065574480739, 0.9329685900413733, 0.661433964801116, 0.9468031896359194] | [0.9475010076582023, 0.9648201943117868, 0.7779515729284813, 0.9726341721543897] |
| 0.1047 | 5.0 | 800 | 0.1260 | 0.8447 | 0.9060 | 0.9643 | [0.8581731584290526, 0.9316708017224354, 0.6429457606853357, 0.9461543989839276] | [0.9425328146084153, 0.9716290009653072, 0.7414471782174548, 0.9684613946705924] |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.10.1
- Tokenizers 0.13.2
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