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Dimasnoufal/image_classification

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

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image_classification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.0801
  • —Accuracy: 0.675

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: 6e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log1.0231.09170.625
No log2.0461.16050.6125
No log3.0691.05430.6375
No log4.0921.16630.6
No log5.01151.25460.5875
No log6.01381.05800.6
No log7.01611.11930.6125
No log8.01841.22970.525
No log9.02071.22950.55
No log10.02301.08420.6125

Framework versions

  • —Transformers 4.35.2
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.17.0
  • —Tokenizers 0.15.1