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swinv2-tiny-patch4-window8-256-Diabetic-Retinopathy-DA

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6974
  • Accuracy: 0.8091

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: 40

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.5987 1.0 23 1.5683 0.4909
1.4137 2.0 46 1.2639 0.4909
1.1988 3.0 69 0.8726 0.7636
0.8533 4.0 92 0.6361 0.7545
0.8042 5.0 115 0.5985 0.7545
0.7349 6.0 138 0.5943 0.7545
0.7003 7.0 161 0.5178 0.7636
0.6641 8.0 184 0.5058 0.7545
0.641 9.0 207 0.5092 0.7909
0.6571 10.0 230 0.5319 0.7636
0.6522 11.0 253 0.5726 0.7909
0.5659 12.0 276 0.5490 0.7727
0.5511 13.0 299 0.5465 0.8
0.5435 14.0 322 0.5728 0.7909
0.5259 15.0 345 0.6047 0.7636
0.5496 16.0 368 0.6479 0.7818
0.543 17.0 391 0.6040 0.7727
0.4646 18.0 414 0.6269 0.7818
0.4867 19.0 437 0.6535 0.7909
0.4357 20.0 460 0.6991 0.7727
0.4392 21.0 483 0.7127 0.7636
0.4403 22.0 506 0.6974 0.8091
0.4358 23.0 529 0.6883 0.7818
0.4094 24.0 552 0.6768 0.8
0.3913 25.0 575 0.7270 0.7636
0.3686 26.0 598 0.7104 0.7727
0.3679 27.0 621 0.7115 0.7818
0.378 28.0 644 0.8020 0.8091
0.3583 29.0 667 0.7524 0.7909
0.3299 30.0 690 0.7783 0.7909
0.3672 31.0 713 0.8193 0.7909
0.3567 32.0 736 0.8095 0.7909
0.3585 33.0 759 0.8324 0.7909
0.3191 34.0 782 0.8042 0.7909
0.3144 35.0 805 0.8189 0.7909
0.3452 36.0 828 0.8377 0.7909
0.3263 37.0 851 0.8204 0.7909
0.2939 38.0 874 0.8103 0.7909
0.3152 39.0 897 0.8184 0.7818
0.2787 40.0 920 0.8241 0.7818

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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