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swin-tiny-patch4-window7-224-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: 0.2469
  • Accuracy: 0.9383

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: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.9843 0.99 43 0.8500 0.6948
0.5335 2.0 87 0.5584 0.7825
0.4263 2.99 130 0.4791 0.8117
0.3308 4.0 174 0.4269 0.8344
0.2882 4.99 217 0.3567 0.8636
0.2517 6.0 261 0.3317 0.8701
0.1908 6.99 304 0.3082 0.8815
0.187 8.0 348 0.3230 0.8799
0.1434 8.99 391 0.3323 0.9010
0.1277 10.0 435 0.2489 0.9075
0.156 10.99 478 0.3246 0.8880
0.0781 12.0 522 0.3121 0.9010
0.1001 12.99 565 0.2708 0.9058
0.0892 14.0 609 0.2582 0.9140
0.0644 14.99 652 0.2486 0.9221
0.0689 16.0 696 0.2465 0.9237
0.0547 16.99 739 0.2402 0.9334
0.0597 18.0 783 0.2534 0.9237
0.0512 18.99 826 0.2400 0.9318
0.041 20.0 870 0.2397 0.9286
0.0376 20.99 913 0.2663 0.9269
0.0412 22.0 957 0.3026 0.9221
0.0423 22.99 1000 0.2678 0.9302
0.0266 24.0 1044 0.2510 0.9318
0.0313 24.99 1087 0.2542 0.9334
0.0207 26.0 1131 0.2743 0.9334
0.0292 26.99 1174 0.2614 0.9318
0.0242 28.0 1218 0.2469 0.9383
0.0201 28.99 1261 0.2534 0.9367
0.0354 29.66 1290 0.2525 0.9367

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.1
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Model size
27.6M params
Tensor type
I64
·
F32
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Finetuned from

Evaluation results