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ALM-AHME/beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd

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-Shuffled-3rd

This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0488
  • —Accuracy: 0.9901

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
1.98351.01141.92960.2315
1.60452.02291.43340.5172
1.05253.03430.92980.6962
0.7954.04580.65800.7709
0.57395.05720.47170.8366
0.58216.06870.35110.8851
0.45667.08010.27050.9204
0.27518.09160.21140.9384
0.23529.010300.13030.9688
0.183110.011450.11940.9688
0.151511.012590.06730.9869
0.20411.9513680.04880.9901

Framework versions

  • —Transformers 4.31.0
  • —Pytorch 2.0.1+cu118
  • —Datasets 2.14.4
  • —Tokenizers 0.13.3