Hugging Face's logo

Ventalik
/
segformer_rust

Transformers
PyTorch
segformer
generated_from_trainer
Inference Endpoints
Model card Files Community
1
Ventalik commited on
Commit
71bfc6a
•
1 Parent(s): 0df0ebc

End of training

Browse files
Files changed (1) hide show
  1. README.md +38 -38
README.md CHANGED
@@ -15,12 +15,12 @@ should probably proofread and complete it, then remove this comment. -->
15
 
16
  This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
- - Loss: 0.1438
19
- - Mean Iou: 0.7943
20
- - Mean Accuracy: 0.8621
21
- - Overall Accuracy: 0.9463
22
- - Per Category Iou: [0.9404316292856895, 0.6481512759943856]
23
- - Per Category Accuracy: [0.9766097421311045, 0.7476136089750051]
24
 
25
  ## Model description
26
 
@@ -49,38 +49,38 @@ The following hyperparameters were used during training:
49
 
50
  ### Training results
51
 
52
- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
53
- |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------:|:----------------------------------------:|
54
- | 0.2683 | 1.0 | 514 | 0.1919 | 0.7319 | 0.8203 | 0.9254 | [0.9180806580950376, 0.5456807971830461] | [0.9632417779264837, 0.6772761097220785] |
55
- | 0.2221 | 2.0 | 1028 | 0.1848 | 0.7247 | 0.7906 | 0.9285 | [0.9222502676042136, 0.5272319457425635] | [0.9780221080448669, 0.6032531950921799] |
56
- | 0.2051 | 3.0 | 1542 | 0.1798 | 0.7523 | 0.8476 | 0.9301 | [0.9226057238240142, 0.5819673887381934] | [0.9598172268335441, 0.7353887410800054] |
57
- | 0.1996 | 4.0 | 2056 | 0.1662 | 0.7530 | 0.8151 | 0.9366 | [0.9305887422755489, 0.5753549591140691] | [0.9802446445708194, 0.6499256145141094] |
58
- | 0.1878 | 5.0 | 2570 | 0.1613 | 0.7695 | 0.8443 | 0.9386 | [0.9321977696827667, 0.6067612442121683] | [0.972541727740175, 0.7160658070940397] |
59
- | 0.1848 | 6.0 | 3084 | 0.1579 | 0.7659 | 0.8299 | 0.9395 | [0.9335431699668292, 0.5982432303010027] | [0.9789606327074537, 0.6808199676860336] |
60
- | 0.1739 | 7.0 | 3598 | 0.1543 | 0.7799 | 0.8516 | 0.9419 | [0.9357233119518715, 0.6240100443072397] | [0.9744037993799354, 0.7287987165292924] |
61
- | 0.1742 | 8.0 | 4112 | 0.1607 | 0.7737 | 0.8667 | 0.9369 | [0.9296752366973121, 0.6176824708083143] | [0.9620707480253384, 0.7713870499643393] |
62
- | 0.1631 | 9.0 | 4626 | 0.1553 | 0.7803 | 0.8636 | 0.9402 | [0.9335684843016983, 0.626952054351963] | [0.9678138198093251, 0.7593407854928076] |
63
- | 0.1631 | 10.0 | 5140 | 0.1564 | 0.7679 | 0.8406 | 0.9386 | [0.9322118932460649, 0.6035637849191774] | [0.9738013828280326, 0.7073043940670594] |
64
- | 0.1577 | 11.0 | 5654 | 0.1499 | 0.7836 | 0.8520 | 0.9434 | [0.9373956576514434, 0.6297874494960901] | [0.9763014923228973, 0.7277053858903674] |
65
- | 0.1522 | 12.0 | 6168 | 0.1515 | 0.7781 | 0.8454 | 0.9422 | [0.9361248378060324, 0.6200926437502748] | [0.9769566337905029, 0.7138379976069665] |
66
- | 0.1486 | 13.0 | 6682 | 0.1531 | 0.7766 | 0.8485 | 0.9410 | [0.9347900233191081, 0.618411826576312] | [0.9743083731504567, 0.7226475641364578] |
67
- | 0.146 | 14.0 | 7196 | 0.1568 | 0.7835 | 0.8667 | 0.9412 | [0.9345511743761084, 0.6325140238903502] | [0.9679584694275379, 0.7654769806378111] |
68
- | 0.1453 | 15.0 | 7710 | 0.1485 | 0.7837 | 0.8473 | 0.9442 | [0.938357945982732, 0.6290898844632448] | [0.9790292010707323, 0.7156414504087399] |
69
- | 0.1439 | 16.0 | 8224 | 0.1492 | 0.7896 | 0.8623 | 0.9444 | [0.9382510027549076, 0.6409378390750833] | [0.973914066583286, 0.7506284726295933] |
70
- | 0.1385 | 17.0 | 8738 | 0.1494 | 0.7790 | 0.8369 | 0.9439 | [0.938230866841315, 0.6196920559815114] | [0.9823649345853678, 0.6913889357135595] |
71
- | 0.1375 | 18.0 | 9252 | 0.1515 | 0.7847 | 0.8549 | 0.9435 | [0.9373782356302373, 0.6321131725666339] | [0.975314658131637, 0.7344851844673589] |
72
- | 0.1353 | 19.0 | 9766 | 0.1450 | 0.7929 | 0.8610 | 0.9459 | [0.9399812074698386, 0.6457742806194801] | [0.9764190916833184, 0.7456795800307741] |
73
- | 0.1317 | 20.0 | 10280 | 0.1453 | 0.7906 | 0.8584 | 0.9453 | [0.9394006951099269, 0.6417152113828789] | [0.9765905703089925, 0.7402706100619615] |
74
- | 0.1292 | 21.0 | 10794 | 0.1565 | 0.7788 | 0.8416 | 0.9431 | [0.9372341895291594, 0.6204583221235739] | [0.9795794314033889, 0.7035825637871398] |
75
- | 0.1284 | 22.0 | 11308 | 0.1487 | 0.7879 | 0.8532 | 0.9450 | [0.9391595949869292, 0.6366277680932542] | [0.9780565365202, 0.7282789363894756] |
76
- | 0.1279 | 23.0 | 11822 | 0.1461 | 0.7927 | 0.8629 | 0.9456 | [0.9395641382795358, 0.6458609695526066] | [0.9752807298744423, 0.7506032283294566] |
77
- | 0.1262 | 24.0 | 12336 | 0.1436 | 0.7934 | 0.8633 | 0.9458 | [0.9398055111519206, 0.6469847970011983] | [0.9754426177792707, 0.7512221554580607] |
78
- | 0.1223 | 25.0 | 12850 | 0.1465 | 0.7945 | 0.8622 | 0.9464 | [0.9404797675363489, 0.6484203969264617] | [0.9766238155760367, 0.7478641586538628] |
79
- | 0.1234 | 26.0 | 13364 | 0.1435 | 0.7925 | 0.8570 | 0.9463 | [0.9405453729701521, 0.6444525239879496] | [0.9784625404961454, 0.735513574144182] |
80
- | 0.1223 | 27.0 | 13878 | 0.1464 | 0.7937 | 0.8618 | 0.9461 | [0.9402290147962161, 0.6472276210560935] | [0.976462283595653, 0.7471743581526247] |
81
- | 0.1196 | 28.0 | 14392 | 0.1450 | 0.7929 | 0.8589 | 0.9462 | [0.9403789254222912, 0.645380249186489] | [0.9776359685007636, 0.7400721898628863] |
82
- | 0.1199 | 29.0 | 14906 | 0.1451 | 0.7919 | 0.8563 | 0.9462 | [0.9403753807784087, 0.6433302809940281] | [0.9784796056303284, 0.7341607320998506] |
83
- | 0.1208 | 30.0 | 15420 | 0.1438 | 0.7943 | 0.8621 | 0.9463 | [0.9404316292856895, 0.6481512759943856] | [0.9766097421311045, 0.7476136089750051] |
84
 
85
 
86
  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 0.1989
19
+ - Mean Iou: 0.4909
20
+ - Mean Accuracy: 0.5770
21
+ - Overall Accuracy: 0.9351
22
+ - Per Category Iou: [0.9330033577422647, 0.43802844257518975, 0.10174998526948427]
23
+ - Per Category Accuracy: [0.964764208993714, 0.619516063444351, 0.14676017920088064]
24
 
25
  ## Model description
26
 
 
49
 
50
  ### Training results
51
 
52
+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
53
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------------------------------------------------------:|:---------------------------------------------------------------:|
54
+ | 0.3245 | 1.0 | 288 | 0.2058 | 0.3737 | 0.4006 | 0.9292 | [0.928254594835728, 0.19278478772636354, 0.0] | [0.9934403780274128, 0.20834926267819698, 0.0] |
55
+ | 0.2376 | 2.0 | 576 | 0.2186 | 0.4440 | 0.5394 | 0.9205 | [0.9174093139660287, 0.3952780826522951, 0.019450366169241784] | [0.9466914641620554, 0.6519016208812702, 0.019680530318053235] |
56
+ | 0.2267 | 3.0 | 864 | 0.1989 | 0.4456 | 0.5055 | 0.9349 | [0.932781347474167, 0.4035973409203434, 0.0003156374054605271] | [0.9714340031497313, 0.5447040039563373, 0.0003156655078774732] |
57
+ | 0.2227 | 4.0 | 1152 | 0.1916 | 0.4707 | 0.5302 | 0.9370 | [0.9346588332598218, 0.4138838160094419, 0.06341712806343888] | [0.9731864476801606, 0.54656085524886, 0.07078191965098726] |
58
+ | 0.2144 | 5.0 | 1440 | 0.1896 | 0.4891 | 0.5724 | 0.9328 | [0.9302444676641086, 0.43202079299936413, 0.10517087813054486] | [0.9610582832573524, 0.6347191782872807, 0.12137743477257919] |
59
+ | 0.2003 | 6.0 | 1728 | 0.2024 | 0.4630 | 0.5614 | 0.9260 | [0.9229095306993824, 0.428931900333899, 0.037186726485148515] | [0.9487448882036036, 0.6966673460182111, 0.03891184433643468] |
60
+ | 0.1941 | 7.0 | 2016 | 0.2073 | 0.4860 | 0.5888 | 0.9219 | [0.918639874525932, 0.4060024340936176, 0.13340049908214777] | [0.9461779703553824, 0.669512151538538, 0.15057649425124547] |
61
+ | 0.1867 | 8.0 | 2304 | 0.1807 | 0.4634 | 0.5301 | 0.9372 | [0.9349180068188713, 0.43659922555690217, 0.018734234161859927] | [0.9689566528873623, 0.602518494621371, 0.018875178573596604] |
62
+ | 0.1854 | 9.0 | 2592 | 0.1921 | 0.4725 | 0.5473 | 0.9345 | [0.9321974693686552, 0.43270280485825646, 0.052579663560228966] | [0.9642507962436797, 0.6216561173996741, 0.05587279489431276] |
63
+ | 0.18 | 10.0 | 2880 | 0.1847 | 0.4771 | 0.5591 | 0.9335 | [0.9311550048182651, 0.4407180368387474, 0.05928079306817498] | [0.9605858689552134, 0.6528219329451048, 0.06379276154708474] |
64
+ | 0.1838 | 11.0 | 3168 | 0.1887 | 0.4652 | 0.5400 | 0.9344 | [0.9321143595621934, 0.43344353554824266, 0.02996913887506222] | [0.9638921692510604, 0.6257803286194064, 0.030457674516485428] |
65
+ | 0.1852 | 12.0 | 3456 | 0.1873 | 0.4783 | 0.5588 | 0.9338 | [0.931356267339074, 0.43971228563091297, 0.06380926339455255] | [0.9613249758102673, 0.6471117095414763, 0.06799758799176032] |
66
+ | 0.1682 | 13.0 | 3744 | 0.1778 | 0.4578 | 0.5035 | 0.9411 | [0.939396147353813, 0.410371405648735, 0.023504333548772998] | [0.981291057821883, 0.5056175933375897, 0.023695148059264176] |
67
+ | 0.1793 | 14.0 | 4032 | 0.1728 | 0.4720 | 0.5296 | 0.9402 | [0.938163188412165, 0.436672912065328, 0.04117603263361246] | [0.974742378495531, 0.5715719389819965, 0.042525809702262676] |
68
+ | 0.178 | 15.0 | 4320 | 0.1825 | 0.4794 | 0.5492 | 0.9369 | [0.9348434866894885, 0.42443186583904435, 0.07881529998132747] | [0.9714614165049668, 0.5650121075899666, 0.11103331889905584] |
69
+ | 0.1651 | 16.0 | 4608 | 0.1912 | 0.4640 | 0.5322 | 0.9362 | [0.9340976310450665, 0.4306683229566104, 0.02708604107096439] | [0.9679043107574059, 0.6011619809118315, 0.02741028826736059] |
70
+ | 0.1761 | 17.0 | 4896 | 0.1757 | 0.4724 | 0.5310 | 0.9389 | [0.9368263731599995, 0.42525112196356074, 0.055183904634890216] | [0.9744989654092739, 0.5559049976770041, 0.06246130062283233] |
71
+ | 0.1633 | 18.0 | 5184 | 0.1917 | 0.4620 | 0.5384 | 0.9354 | [0.9330768754070563, 0.44480333780621734, 0.00820601828493007] | [0.9636645135753821, 0.6433031553142516, 0.008227538173267988] |
72
+ | 0.1641 | 19.0 | 5472 | 0.1875 | 0.5028 | 0.5812 | 0.9354 | [0.9331706683726091, 0.4415413111697262, 0.133770201971674] | [0.9634674000411962, 0.6392245347005364, 0.1408556154060956] |
73
+ | 0.1629 | 20.0 | 5760 | 0.1793 | 0.4675 | 0.5268 | 0.9393 | [0.9374054652680682, 0.4330992564780264, 0.03193276637035433] | [0.973550456833595, 0.5746419640278527, 0.032230257753028166] |
74
+ | 0.1562 | 21.0 | 6048 | 0.2019 | 0.4716 | 0.5546 | 0.9325 | [0.9300698286146659, 0.43671042563474527, 0.04809297394799092] | [0.9592354491418064, 0.6554619381223432, 0.049203349291978456] |
75
+ | 0.1626 | 22.0 | 6336 | 0.1970 | 0.4814 | 0.5547 | 0.9367 | [0.9344970508696149, 0.4450380854494638, 0.06452712765123607] | [0.9658097423660128, 0.6317005392634606, 0.066633751117982] |
76
+ | 0.1568 | 23.0 | 6624 | 0.1956 | 0.4917 | 0.5775 | 0.9355 | [0.9330854195306507, 0.4390415550387406, 0.10283427594052297] | [0.9658042305145758, 0.6119827953416446, 0.15474894474639514] |
77
+ | 0.1595 | 24.0 | 6912 | 0.1817 | 0.4769 | 0.5411 | 0.9383 | [0.9362300601150796, 0.4346106438489147, 0.05977008091938032] | [0.9712496965644727, 0.586809439959973, 0.06537513608016285] |
78
+ | 0.1539 | 25.0 | 7200 | 0.1893 | 0.4825 | 0.5650 | 0.9358 | [0.933537238237644, 0.4394361715176897, 0.07460055177704666] | [0.9667388784050233, 0.6055558721569863, 0.12278174158326487] |
79
+ | 0.1521 | 26.0 | 7488 | 0.1933 | 0.4841 | 0.5721 | 0.9355 | [0.9332085743268924, 0.44365656488299987, 0.07547064782962047] | [0.9657158949896331, 0.6132794230856533, 0.13717285114752506] |
80
+ | 0.1468 | 27.0 | 7776 | 0.2049 | 0.4861 | 0.5735 | 0.9327 | [0.9304477363857275, 0.43790721804897553, 0.08980648951011608] | [0.9595730176196706, 0.6520673697794168, 0.10889650623034679] |
81
+ | 0.1534 | 28.0 | 8064 | 0.1950 | 0.4976 | 0.5800 | 0.9355 | [0.9333228433994155, 0.4429051769820105, 0.11658642467846855] | [0.9637939610275141, 0.636643256405625, 0.13955248343767832] |
82
+ | 0.1478 | 29.0 | 8352 | 0.2049 | 0.4913 | 0.5841 | 0.9344 | [0.9322490633597582, 0.4375642417642195, 0.10407288263883356] | [0.9639606458995019, 0.6190808277013159, 0.169160289279109] |
83
+ | 0.1414 | 30.0 | 8640 | 0.1989 | 0.4909 | 0.5770 | 0.9351 | [0.9330033577422647, 0.43802844257518975, 0.10174998526948427] | [0.964764208993714, 0.619516063444351, 0.14676017920088064] |
84
 
85
 
86
  ### Framework versions