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Electrcical-IMAGE-finetuned-eurosat

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

  • Loss: 0.3583
  • Accuracy: 0.8960

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • 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
1.6143 0.98 28 1.2882 0.5347
0.8597 2.0 57 0.7302 0.7649
0.5858 2.98 85 0.4849 0.8465
0.4332 4.0 114 0.4274 0.8614
0.4054 4.98 142 0.3687 0.8787
0.3826 6.0 171 0.3788 0.8614
0.3561 6.98 199 0.3700 0.8936
0.2838 8.0 228 0.3550 0.8812
0.2897 8.98 256 0.3698 0.8886
0.2519 10.0 285 0.3459 0.8837
0.2194 10.98 313 0.3583 0.8960
0.1955 12.0 342 0.3442 0.8886
0.2443 12.98 370 0.3801 0.8787
0.207 14.0 399 0.3499 0.8861
0.2078 14.98 427 0.3701 0.8837
0.1873 16.0 456 0.3773 0.8861
0.1697 16.98 484 0.3753 0.8861
0.1812 18.0 513 0.3747 0.8911
0.151 18.98 541 0.3736 0.8861
0.1567 19.65 560 0.3726 0.8861

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Finetuned from

Evaluation results