CoolFace
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toukapy/detr_domain_shift

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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detrdomainshift

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.4246
  • —Map: 0.8353
  • —Map 50: 0.9529
  • —Map 75: 0.9029
  • —Map Small: 0.0159
  • —Map Medium: 0.6742
  • —Map Large: 0.8707
  • —Mar 1: 0.7106
  • —Mar 10: 0.8977
  • —Mar 100: 0.9152
  • —Mar Small: 0.2984
  • —Mar Medium: 0.8276
  • —Mar Large: 0.9365
  • —Map Garbage bag: 0.8185
  • —Mar 100 Garbage bag: 0.9059
  • —Map Paper bag: 0.8446
  • —Mar 100 Paper bag: 0.9239
  • —Map Plastic bag: 0.8429
  • —Mar 100 Plastic bag: 0.9159

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: 0.0001
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —num_epochs: 50

Training results

Training LossEpochStepValidation LossMapMap 50Map 75Map SmallMap MediumMap LargeMar 1Mar 10Mar 100Mar SmallMar MediumMar LargeMap Garbage bagMar 100 Garbage bagMap Paper bagMar 100 Paper bagMap Plastic bagMar 100 Plastic bag
0.97751.015570.87390.24190.32760.27190.00030.18080.25660.42460.7730.81860.02710.68490.85010.19990.8080.30450.82920.22130.8187
0.9192.031140.85270.44650.60370.50180.00430.28770.47870.50980.76270.81370.01230.66560.84740.54960.80750.45180.82350.33820.8101
0.853.046710.76490.55080.72680.61830.00130.36840.58980.56190.79440.83350.06520.71470.86130.56350.82060.58770.84710.50120.8327
0.8444.062280.75620.6050.79240.68570.00230.44020.64050.57320.79010.82960.05790.71740.8560.61130.82130.61250.83640.59120.8313
0.83325.077850.78110.59820.80040.67990.0070.41410.63650.56830.78010.82140.01940.69140.8520.57850.80910.63260.83610.58340.8188
0.93036.093420.93250.51790.73950.59060.00010.36650.55060.51920.72880.77560.00970.63580.80740.520.76640.57440.78250.45930.7778
0.87737.0108990.88690.55610.77480.6260.00.3740.59480.5470.7480.78950.00.64830.82230.54350.77520.59090.81320.53390.7801
1.0118.0124560.87290.56040.79450.64370.00130.39910.59540.5380.74750.79710.02180.64890.8310.52510.77290.61520.82220.5410.7962
1.00199.0140131.21870.3130.52580.33960.00.20260.3370.38590.61180.68920.00.51410.72820.43950.70760.24960.69160.250.6685
0.928610.0155700.80590.58480.78520.65840.00.38740.62570.55950.77250.81960.01790.66890.85390.57620.80150.62390.84290.55440.8143
0.878211.0171270.84580.55870.75510.6270.010.3770.5960.55510.76780.8120.05160.66350.84530.57260.79660.61640.83550.48720.804
0.849312.0186840.78720.58990.77870.66220.00120.38030.63290.570.78320.82870.0190.67190.86430.58130.82150.63360.84120.55480.8235
0.79313.0202410.77840.61120.81280.69240.00230.42750.65020.57850.77830.82490.04340.68720.85660.61570.82530.63260.83440.58520.8151
0.771214.0217980.78810.60890.81620.6880.00010.42110.64970.57720.77850.81840.0390.68740.84910.59840.8030.64290.840.58530.8123
0.789215.0233550.72040.65480.85150.7420.00070.4860.69160.60180.79910.83760.03590.71390.86680.6530.83770.67160.84470.63990.8302
0.773516.0249120.77680.6040.79080.68070.01520.41420.64450.58030.77940.82580.0430.71670.85220.58540.83590.64210.83070.58440.8106
0.805217.0264690.74660.63890.84170.73250.00010.46580.67670.58830.78470.82310.02450.72910.84690.64930.82620.65720.83290.61010.8101
0.736618.0280260.74900.63720.84350.71980.00690.44920.67830.58830.78810.82870.02710.70840.85720.64270.83070.64860.83760.62020.8178
0.731619.0295830.69640.66970.8690.75780.00280.50950.7040.60680.80290.8390.07050.72830.86510.65290.82770.69150.85380.66460.8353
0.724320.0311400.71650.66160.86050.7530.00330.47820.70030.60460.79720.82990.05810.71480.85740.63660.81260.67910.84520.66920.832
0.718921.0326970.69210.67480.86940.76210.0010.50190.71210.61050.80420.83820.07880.72530.86490.64220.82410.70870.85810.67350.8324
0.680222.0342540.63810.70910.8860.78750.00070.53660.74650.63180.82910.86180.07160.7520.88830.69530.85720.72530.87180.70670.8565
0.667623.0358110.62520.71860.88650.79940.00340.54230.75730.63910.83730.86490.06650.75970.89080.70210.85670.73580.87520.71810.8628
0.662424.0373680.64320.71170.89860.80410.00190.53840.74880.630.82050.85350.09740.74920.87860.68710.83940.72870.86390.71940.8572
0.635625.0389250.61010.72840.9050.81780.0040.54440.76760.64480.83220.8630.11080.76160.88740.71250.85560.74170.87090.73110.8626
0.631926.0404820.63300.71910.90050.81130.00850.5570.7540.63920.82620.85130.1060.75660.87450.7020.8490.73710.85580.71820.8489
0.606927.0420390.58550.74610.90720.8240.00820.56150.78520.65120.8450.87420.24840.76250.90030.71590.85960.76150.8840.76090.8791
0.589828.0435960.55820.75810.91580.84050.00910.58440.79570.66490.85520.8780.24740.7850.90080.73840.86770.77420.88820.76160.8782
0.577729.0451530.54120.77060.92260.84920.00290.61170.80540.67180.85910.88780.21470.78820.91180.75420.88260.77990.89530.77770.8854
0.546130.0467100.54240.77140.92590.85630.00240.60330.80810.67080.85710.88290.2060.78230.90690.76020.87840.78140.89060.77260.8798
0.539231.0482670.52740.77730.92190.85910.00260.59860.81590.67520.86480.88880.28320.7950.91110.75490.88350.79020.8940.78670.8889
0.536732.0498240.51810.78630.93120.86540.00380.62340.82160.6780.86630.88820.23320.79560.91090.76890.88050.79850.89620.79150.8879
0.518733.0513810.50790.78530.9340.86720.01870.62450.82060.68140.86810.89170.24120.79840.91430.76920.890.79370.89660.79310.8884
0.510234.0529380.48610.80490.93810.87610.03180.64810.83880.69120.88110.90470.26590.8180.92620.78930.89910.81910.9140.80620.901
0.486835.0544950.47530.80460.93920.88270.00840.63890.84130.69330.87960.90150.24950.80560.92490.78840.89810.8110.90360.81430.903
0.482136.0560520.47140.80960.94270.88610.02250.64850.84480.69550.88280.90420.2780.81590.92580.79230.89810.82210.91210.81430.9024
0.471437.0576090.44470.82320.94330.89110.02190.66190.85990.70320.89350.91260.2690.82350.93440.80720.90510.82950.91730.83290.9154
0.465338.0591660.45540.8190.9460.89120.01780.65670.85480.70210.88730.90590.30040.81380.92810.80250.8990.82810.91220.82640.9065
0.449439.0607230.43100.83080.94510.89390.02430.66850.86630.70910.89850.9180.32420.83580.93810.81270.91140.84010.92370.83970.919
0.438940.0622800.42890.83360.94890.89670.01770.67570.86840.71020.89760.91650.29580.83290.93690.81670.91020.84250.92190.84160.9174
0.437641.0638370.42450.83650.94980.90110.01790.67950.87090.71220.89850.91820.33350.83820.93770.81670.90670.84770.92720.8450.9205
0.425242.0653940.42440.83680.95110.89980.01750.68020.87130.71060.89880.91660.36040.83310.93690.81830.90890.84670.92290.84560.9179
0.421543.0669510.42810.83420.95170.89870.02970.67310.86960.70880.89850.91590.31760.830.93690.81770.90920.84310.92170.84180.9169
0.427944.0685080.42350.83750.95270.90120.01910.67770.8730.71160.89840.91640.320.82880.93760.81910.90940.84790.92260.84530.9172
0.413345.0700650.42200.8370.95250.90140.01680.67640.87190.71170.90.91750.30590.83530.93770.81680.90810.84880.92440.84550.9199
0.408546.0716220.42310.8370.95380.90260.01580.6790.87210.71180.89860.91570.29050.82760.93710.81960.9080.84630.92270.84510.9165
0.413847.0731790.42690.83350.95290.90190.0140.67350.86890.70970.89650.91410.29540.82460.93580.81450.90480.84360.92260.84240.9149
0.414748.0747360.42460.83530.95290.90230.01580.67360.87090.71080.89790.91550.29820.82660.9370.81820.90620.84470.92420.8430.916
0.414549.0762930.42370.83620.95310.90270.01590.67510.87150.71080.89840.9160.29840.82860.93730.81920.90670.84540.92480.84390.9167
0.40650.0778500.42460.83530.95290.90290.01590.67420.87070.71060.89770.91520.29840.82760.93650.81850.90590.84460.92390.84290.9159

Framework versions

  • —Transformers 4.49.0
  • —Pytorch 2.5.1+cu118
  • —Datasets 3.3.2
  • —Tokenizers 0.21.0