CoolFace
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Marc-HealthAI/FetalPlane_Classifcation-6-V2

sourceHugging Faceupdated 10d agoView on Hugging Face
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Model Card

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FetalPlane_Classifcation-6-V2

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2863
  • —Accuracy: 0.9091
  • —Precision Macro: 0.8809
  • —Recall Macro: 0.9155
  • —F1 Macro: 0.8947

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: 0.0001985679720704591
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 32
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —num_epochs: 100
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecision MacroRecall MacroF1 Macro
No log1.02420.53750.79470.77260.81190.7775
No log2.04840.43220.83270.79360.84930.8152
0.60993.07260.47420.78870.77400.83880.7832
0.60994.09680.39310.83470.79500.85700.8171
0.55375.012100.40780.83310.81000.85410.8225
0.55376.014520.37030.85780.82450.86730.8415
0.49867.016940.39240.83920.81100.86370.8258
0.49868.019360.36030.86630.83320.88010.8517
0.44869.021780.36750.86550.82900.88380.8494
0.448610.024200.37440.85010.81400.87960.8334
0.423811.026620.35030.86300.82230.88280.8442
0.423812.029040.39090.86460.83030.88230.8483
0.409413.031460.32710.87840.83880.89290.8594
0.409414.033880.32490.88120.84460.89320.8639
0.387515.036300.33010.88160.85540.89000.8683
0.387516.038720.34080.87520.84370.89430.8622
0.366217.041140.31210.88120.84350.89910.8648
0.366218.043560.32880.87310.83460.89420.8560
0.349119.045980.35770.87030.83360.88230.8513
0.349120.048400.33480.88080.84290.89460.8624
0.347621.050820.30890.89090.86500.89090.8757
0.347622.053240.32950.89900.87870.89130.8839
0.322623.055660.29540.88970.85510.90030.8734
0.322624.058080.30970.89490.87100.88960.8793
0.320825.060500.29220.89860.86990.89980.8830
0.320826.062920.31170.89330.86850.89340.8796
0.307027.065340.31570.88930.85630.90130.8746
0.307028.067760.29620.88930.85510.90300.8746
0.295029.070180.31380.88690.85350.90680.8725
0.295030.072600.30030.89900.86880.90430.8834
0.295331.075020.31050.88730.85390.90160.8724
0.295332.077440.27760.89940.86700.90950.8847
0.295333.079860.29800.90060.87600.89930.8866
0.288634.082280.28080.89820.86630.90770.8838
0.288635.084700.29640.90020.87420.89850.8844
0.272136.087120.28700.90340.87590.91080.8910
0.272137.089540.29390.89900.87440.90350.8872
0.260738.091960.28820.90140.87500.91070.8901
0.260739.094380.30700.90180.87620.90210.8879
0.268840.096800.28010.90300.87730.90900.8909
0.268841.099220.28420.90100.87460.90480.8878
0.250942.0101640.28920.88810.85680.90190.8751
0.250943.0104060.28360.90300.87820.90570.8901
0.244644.0106480.28120.90460.87500.90770.8886
0.244645.0108900.28730.89010.85680.90560.8764
0.245646.0111320.28630.90910.88090.91550.8947
0.245647.0113740.31090.90020.87420.90350.8865
0.227948.0116160.29380.90460.87830.90620.8902
0.227949.0118580.30840.90300.87590.89900.8864
0.231750.0121000.29540.90100.87030.90930.8866
0.231751.0123420.27710.90460.87500.91010.8904
0.218452.0125840.28500.90380.87670.90350.8887
0.218453.0128260.27920.90510.87720.90710.8904
0.210054.0130680.28920.90380.87540.90420.8883
0.210055.0133100.27300.90550.87410.91250.8905
0.212456.0135520.30550.90300.87890.90130.8890

Framework versions

  • —Transformers 5.17.0
  • —Pytorch 2.11.0+cu128
  • —Datasets 5.0.1
  • —Tokenizers 0.23.1