CoolFace
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PREMAADC/vit-base-ham10000

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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Model Card

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vit-base-ham10000

This model is a fine-tuned version of google/vit-base-patch16-224 on the HAM10000 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5809
  • Accuracy: 0.7848

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: 0.0003
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracy
0.68981.05010.67880.7474
0.59142.010020.62370.7664
0.62283.015030.60050.7763
0.58434.020040.58550.7848
0.55695.025050.58090.7848

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2