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swin-small-patch4-window7-224-finetuned-piid

This model is a fine-tuned version of microsoft/swin-small-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6168
  • Accuracy: 0.7763

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
1.2327 0.98 20 1.1687 0.5114
0.7354 2.0 41 0.7696 0.6712
0.602 2.98 61 0.7198 0.7078
0.5809 4.0 82 0.5824 0.7397
0.4989 4.98 102 0.5331 0.7489
0.4364 6.0 123 0.6137 0.7489
0.3321 6.98 143 0.5839 0.7717
0.3 8.0 164 0.5246 0.7763
0.3024 8.98 184 0.5557 0.7717
0.3433 10.0 205 0.5258 0.7900
0.258 10.98 225 0.6354 0.7489
0.1595 12.0 246 0.5492 0.8219
0.2295 12.98 266 0.5889 0.7900
0.1956 14.0 287 0.5670 0.7900
0.2028 14.98 307 0.5460 0.7900
0.1514 16.0 328 0.6587 0.7900
0.0934 16.98 348 0.6131 0.7945
0.1323 18.0 369 0.6615 0.7900
0.1213 18.98 389 0.6192 0.7671
0.1028 19.51 400 0.6168 0.7763

Framework versions

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