Image Classification
timm
PyTorch
Safetensors
vision-transformer
swin
gravitational-lensing
strong-lensing
astronomy
astrophysics
Eval Results (legacy)
Instructions to use parlange/swin-gravit-b2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use parlange/swin-gravit-b2 with timm:
import timm model = timm.create_model("hf_hub:parlange/swin-gravit-b2", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download training_metrics.csv from parlange/swin-gravit-b2: direct link, hf CLI and curl.
- Browser
- Download file 4.63 kB
-
https://huggingface.co/parlange/swin-gravit-b2/resolve/main/training_metrics.csv
- Command line
-
hf download hf://parlange/swin-gravit-b2/training_metrics.csv
-
curl -L -o training_metrics.csv https://huggingface.co/parlange/swin-gravit-b2/resolve/main/training_metrics.csv
4.63 kB
| epoch,train_loss,val_loss,train_accuracy,val_accuracy,train_auc,val_auc,train_f1,val_f1 | |
| 1,0.1439595161093171,0.07619072851452413,0.9438205433611253,0.9742765273311897,0.985845018099286,0.9956001741549865,0.9429878838460874,0.9737991266375546 | |
| 2,0.06839157586968032,0.05810824736138249,0.9775201669769279,0.9807073954983923,0.9957213672199383,0.9970372974270784,0.9773263918522944,0.9804347826086957 | |
| 3,0.061301204017988414,0.05664203580696483,0.9792407062672759,0.9785637727759914,0.9966349095298996,0.9977478176059664,0.9791051555757438,0.9785407725321889 | |
| 4,0.0508239121291516,0.05215318486621526,0.9832176905285722,0.9817792068595927,0.9974244950212321,0.9980298429962928,0.9831076285381711,0.9815016322089227 | |
| 5,0.046795619713773905,0.0694643652419952,0.9842612963276358,0.9817792068595927,0.9978497853193471,0.9973336825623299,0.984167517875383,0.9816612729234089 | |
| 6,0.04491736535484122,0.051700507329591215,0.9847689964460992,0.9817792068595927,0.9981039472356432,0.9979821686431419,0.9846869328493648,0.9818376068376068 | |
| 7,0.040567128453640126,0.05039569819376016,0.9871946747898686,0.9855305466237942,0.9982963678176379,0.997948279645119,0.9871358948203559,0.9854290339989207 | |
| 8,0.036479709491216906,0.06209890508479244,0.9882946917132058,0.977491961414791,0.9986300501031151,0.9980855588066018,0.9882426268521404,0.9775880469583778 | |
| 9,0.03624781207281596,0.05032284864467056,0.9880408416539742,0.9844587352625938,0.9987313734179702,0.9983773488234774,0.9879968293511494,0.9844337090713903 | |
| 10,0.03237894074674547,0.05071818836967661,0.9891126530151746,0.9828510182207931,0.9990181307619153,0.9984037707541393,0.9890651558073654,0.9828693790149893 | |
| 11,0.03247496714671441,0.05087393546219424,0.9892536808258588,0.9833869239013934,0.9990151458443,0.9981033648903087,0.9892058815196759,0.9833601717659689 | |
| 12,0.02969601272056401,0.05961561006556753,0.9900152310035539,0.9844587352625938,0.9992369350879926,0.9980016978962399,0.9899835889310169,0.9844836811128946 | |
| 13,0.026161972048915738,0.08461836112178024,0.9913126868618491,0.984994640943194,0.9994106681127415,0.9971757253681551,0.9912910705197082,0.9849624060150376 | |
| 14,0.03108258543160638,0.07965518330550271,0.9900152310035539,0.9812433011789925,0.9990366814839187,0.9975088714504147,0.9899767823772581,0.9812533476164971 | |
| 15,0.0271319980178464,0.054900352019589045,0.9912562757375755,0.9828510182207931,0.9992575733429979,0.9980286942166989,0.9912275737166789,0.982740021574973 | |
| 16,0.01843444474622573,0.05834010391948308,0.9939075985784397,0.9855305466237942,0.9996814507376787,0.9982262843068667,0.9938934750650232,0.9854760623991393 | |
| 17,0.017260715746670523,0.06006432061122545,0.9943870931347661,0.9860664523043944,0.999694825587079,0.9978184675509972,0.9943742402397309,0.986021505376344 | |
| 18,0.01689717639379492,0.054281585253894905,0.994810176566819,0.9844587352625938,0.9997019314730443,0.9984589121746512,0.9947984395318595,0.984400215169446 | |
| 19,0.01518679453820267,0.06426342092813786,0.9953742878095561,0.9839228295819936,0.9997180000673929,0.9979120930879081,0.9953651367849876,0.9838709677419355 | |
| 20,0.015054562418926668,0.059576416130617885,0.9950640266260506,0.984994640943194,0.9997670968706228,0.9980091649636009,0.9950552400327767,0.9849624060150376 | |
| 21,0.014640409930630129,0.065951001533933,0.994612737631861,0.984994640943194,0.9998151005830203,0.997929324781818,0.9946016223396739,0.9849462365591398 | |
| 22,0.014713315434569805,0.05413568661910545,0.9952896711231455,0.9866023579849946,0.9997829395277107,0.9981504648536627,0.9952794188314441,0.9865663621708759 | |
| 23,0.013743430272975353,0.055943566407421395,0.9954024933716928,0.9866023579849946,0.9998262940240782,0.9981504648536627,0.9953922261484099,0.9865663621708759 | |
| 24,0.012901369380462208,0.05873858389651277,0.9960230157387037,0.9860664523043944,0.9998329750843485,0.9981688453271667,0.996015260703688,0.9860365198711063 | |
| 25,0.013194709263934571,0.05942307736041845,0.9951204377503243,0.9855305466237942,0.9998500778985533,0.9981429977863018,0.9951106463555945,0.9854916711445459 | |
| 26,0.013279275182823095,0.060150547689755245,0.9952332599988718,0.984994640943194,0.9998643724080719,0.9981234685332037,0.9952242348885184,0.9849462365591398 | |
| 27,0.01315793412828805,0.060057299409265304,0.9953742878095561,0.9860664523043944,0.999825891473888,0.9981200221944218,0.9953653987452665,0.9860365198711063 | |
| 28,0.011656034609175529,0.06125851037801271,0.9956845489930615,0.984994640943194,0.9998875803016427,0.9981004929413237,0.9956790646445819,0.9849462365591398 | |
| 29,0.012501262914988924,0.06120557659021145,0.9957127545551983,0.984994640943194,0.999862787665031,0.9981458697352867,0.9957071848169905,0.9849462365591398 | |