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deit-small-patch16-224-finetuned-piid

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

  • Loss: 0.5615
  • Accuracy: 0.7945

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
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.1803 0.98 20 1.0233 0.5753
0.706 2.0 41 0.7299 0.7078
0.6016 2.98 61 0.6877 0.7123
0.4903 4.0 82 0.6139 0.7671
0.4692 4.98 102 0.5667 0.7626
0.374 6.0 123 0.5146 0.8037
0.2995 6.98 143 0.5596 0.7534
0.2905 8.0 164 0.5313 0.7534
0.2612 8.98 184 0.5328 0.7900
0.2499 10.0 205 0.5369 0.7991
0.185 10.98 225 0.5754 0.7808
0.1927 12.0 246 0.5886 0.7717
0.1446 12.98 266 0.5160 0.7991
0.155 14.0 287 0.5353 0.8082
0.1577 14.98 307 0.5848 0.7808
0.1243 16.0 328 0.5572 0.7991
0.1038 16.98 348 0.5859 0.7763
0.1305 18.0 369 0.5752 0.7900
0.0868 18.98 389 0.5616 0.8037
0.1364 19.51 400 0.5615 0.7945

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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Model size
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F32
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Evaluation results