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hanad/Firearms_detection

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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Firearms_detection

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: 0.0580
  • Accuracy: 0.9788

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: 16
  • evalbatchsize: 16
  • seed: 42
  • gradientaccumulationsteps: 4
  • totaltrainbatch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_ratio: 0.1
  • num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracy
0.19160.9903510.16680.9566
0.07112.01030.08570.9757
0.0532.99031540.08030.9757
0.03684.02060.06220.9820
0.05244.95152550.05970.9799

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1