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ALM-AHME/swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-3

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-3

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0112
  • —Accuracy: 0.9951

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: 5e-05
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.5
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
1.18851.01140.87180.6593
0.70372.02280.42080.8637
0.50852.993420.34460.8744
0.28744.04570.20270.9327
0.3555.05710.16660.9401
0.24936.06850.09690.9655
0.19096.997990.05580.9836
0.18218.09140.04120.9901
0.18539.010280.02390.9943
0.06669.9811400.01120.9951

Framework versions

  • —Transformers 4.32.0
  • —Pytorch 2.0.1+cu118
  • —Datasets 2.14.4
  • —Tokenizers 0.13.3