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ALM-AHME/beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20

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

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beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20

This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0434
  • —Accuracy: 0.9908

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-06
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.9
  • —num_epochs: 12

Training results

Training LossEpochStepValidation LossAccuracy
1.96881.01221.84250.2775
1.48222.02441.38330.5457
1.12393.03660.93210.6680
0.86864.04880.66910.7698
0.52345.06100.48720.8335
0.52466.07320.35860.8736
0.36917.08540.31340.8993
0.47088.09760.20690.9394
0.16949.010980.18320.9414
0.274910.012200.11980.9640
0.177711.013420.08450.9733
0.152912.014640.04340.9908

Framework versions

  • —Transformers 4.30.2
  • —Pytorch 2.0.1+cu118
  • —Datasets 2.13.1
  • —Tokenizers 0.13.3