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teacher-status-van-tiny-256-1-2

This model is a fine-tuned version of Visual-Attention-Network/van-tiny on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0859
  • Accuracy: 0.9717
  • F1 Score: 0.9778
  • Recall: 0.9754
  • Precision: 0.9802

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: 128
  • eval_batch_size: 128
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 256
  • 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 F1 Score Recall Precision
0.6722 0.99 33 0.6499 0.6401 0.7806 1.0 0.6401
0.5431 2.0 67 0.4164 0.7817 0.8531 0.9902 0.7494
0.393 2.99 100 0.2833 0.8877 0.9078 0.8639 0.9564
0.354 4.0 134 0.1930 0.9276 0.9436 0.9459 0.9413
0.3007 4.99 167 0.1585 0.9370 0.9511 0.9557 0.9464
0.2898 6.0 201 0.1445 0.9465 0.9581 0.9557 0.9605
0.2824 6.99 234 0.1353 0.9465 0.9580 0.9525 0.9635
0.2763 8.0 268 0.1359 0.9486 0.9603 0.9721 0.9488
0.2473 8.99 301 0.1213 0.9570 0.9664 0.9672 0.9656
0.2598 10.0 335 0.1091 0.9570 0.9665 0.9705 0.9626
0.2476 10.99 368 0.1041 0.9633 0.9714 0.9754 0.9675
0.2376 12.0 402 0.0997 0.9601 0.9686 0.9623 0.9751
0.2402 12.99 435 0.0972 0.9622 0.9704 0.9672 0.9736
0.2324 14.0 469 0.0950 0.9664 0.9739 0.9803 0.9676
0.2256 14.99 502 0.0909 0.9706 0.9770 0.9754 0.9786
0.21 16.0 536 0.0922 0.9622 0.9703 0.9656 0.9752
0.217 16.99 569 0.0933 0.9612 0.9695 0.9656 0.9736
0.2092 18.0 603 0.0891 0.9664 0.9738 0.9754 0.9722
0.2063 18.99 636 0.0913 0.9654 0.9730 0.9738 0.9722
0.2217 20.0 670 0.0917 0.9643 0.9720 0.9672 0.9768
0.1952 20.99 703 0.0859 0.9717 0.9778 0.9754 0.9802
0.2068 22.0 737 0.0907 0.9685 0.9755 0.9770 0.9739
0.1914 22.99 770 0.0847 0.9696 0.9763 0.9787 0.9739
0.1961 24.0 804 0.0870 0.9685 0.9755 0.9770 0.9739
0.1911 24.99 837 0.0884 0.9664 0.9739 0.9770 0.9707
0.1961 26.0 871 0.0870 0.9685 0.9754 0.9738 0.9770
0.1978 26.99 904 0.0871 0.9685 0.9754 0.9754 0.9754
0.1854 28.0 938 0.0858 0.9685 0.9755 0.9770 0.9739
0.1733 28.99 971 0.0860 0.9685 0.9754 0.9738 0.9770
0.1762 29.55 990 0.0858 0.9664 0.9738 0.9738 0.9738

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Evaluation results