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hushem_5x_deit_base_sgd_0001_fold1

This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3736
  • Accuracy: 0.3333

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.4044 1.0 27 1.3857 0.2889
1.4077 2.0 54 1.3850 0.2889
1.4004 3.0 81 1.3845 0.2667
1.4271 4.0 108 1.3839 0.2667
1.3916 5.0 135 1.3834 0.2889
1.3945 6.0 162 1.3828 0.2889
1.3833 7.0 189 1.3824 0.2889
1.3987 8.0 216 1.3819 0.2889
1.3885 9.0 243 1.3815 0.2889
1.4047 10.0 270 1.3810 0.2667
1.3682 11.0 297 1.3806 0.2889
1.3955 12.0 324 1.3802 0.2889
1.3888 13.0 351 1.3799 0.2889
1.3775 14.0 378 1.3795 0.2889
1.3829 15.0 405 1.3792 0.2889
1.3959 16.0 432 1.3788 0.2889
1.3739 17.0 459 1.3785 0.2889
1.3699 18.0 486 1.3782 0.2889
1.3964 19.0 513 1.3779 0.3111
1.3891 20.0 540 1.3776 0.3333
1.3791 21.0 567 1.3773 0.3333
1.3887 22.0 594 1.3770 0.3333
1.3832 23.0 621 1.3768 0.3333
1.3736 24.0 648 1.3765 0.3333
1.3564 25.0 675 1.3763 0.3111
1.3586 26.0 702 1.3761 0.3111
1.3706 27.0 729 1.3758 0.3111
1.3579 28.0 756 1.3756 0.3111
1.3705 29.0 783 1.3754 0.3111
1.3624 30.0 810 1.3752 0.3111
1.367 31.0 837 1.3751 0.3111
1.3534 32.0 864 1.3749 0.3333
1.3672 33.0 891 1.3747 0.3333
1.3654 34.0 918 1.3746 0.3333
1.3592 35.0 945 1.3744 0.3333
1.3511 36.0 972 1.3743 0.3333
1.3644 37.0 999 1.3742 0.3333
1.3508 38.0 1026 1.3741 0.3333
1.3516 39.0 1053 1.3740 0.3333
1.3605 40.0 1080 1.3739 0.3333
1.3566 41.0 1107 1.3739 0.3333
1.3647 42.0 1134 1.3738 0.3333
1.3671 43.0 1161 1.3737 0.3333
1.3471 44.0 1188 1.3737 0.3333
1.3589 45.0 1215 1.3737 0.3333
1.3648 46.0 1242 1.3736 0.3333
1.3521 47.0 1269 1.3736 0.3333
1.365 48.0 1296 1.3736 0.3333
1.3656 49.0 1323 1.3736 0.3333
1.3545 50.0 1350 1.3736 0.3333

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Evaluation results