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swinv2-tiny-patch4-window8-256-finetuned-microbes

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: 1.0939
  • Accuracy: 0.7051

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
4.1153 0.97 16 3.8048 0.1239
3.2047 2.0 33 2.9123 0.2949
2.6979 2.97 49 2.2162 0.4231
1.9422 4.0 66 1.8476 0.5043
1.5677 4.97 82 1.6194 0.5684
1.3485 6.0 99 1.4825 0.5855
1.146 6.97 115 1.4073 0.5983
1.0408 8.0 132 1.2730 0.6325
0.9334 8.97 148 1.2782 0.6282
0.8702 10.0 165 1.1758 0.6752
0.8589 10.97 181 1.1652 0.6838
0.7607 12.0 198 1.2129 0.6795
0.7676 12.97 214 1.1509 0.6795
0.7359 14.0 231 1.1327 0.6966
0.7491 14.97 247 1.1059 0.6966
0.6664 16.0 264 1.1413 0.6923
0.618 16.97 280 1.0954 0.7009
0.6504 18.0 297 1.1030 0.7009
0.6241 18.97 313 1.0956 0.7009
0.6258 19.39 320 1.0939 0.7051

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cpu
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Evaluation results