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hushem_5x_deit_tiny_sgd_0001_fold2

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

  • Loss: 1.5542
  • Accuracy: 0.2

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
1.5719 1.0 27 1.7092 0.2222
1.5311 2.0 54 1.6949 0.2222
1.5151 3.0 81 1.6819 0.2222
1.5077 4.0 108 1.6712 0.2222
1.4707 5.0 135 1.6610 0.2222
1.4799 6.0 162 1.6507 0.2222
1.4704 7.0 189 1.6424 0.2
1.4902 8.0 216 1.6346 0.1778
1.4446 9.0 243 1.6280 0.1778
1.4231 10.0 270 1.6212 0.1778
1.4616 11.0 297 1.6153 0.1778
1.4153 12.0 324 1.6101 0.2
1.4152 13.0 351 1.6055 0.2
1.4531 14.0 378 1.6010 0.2
1.3945 15.0 405 1.5968 0.2
1.3852 16.0 432 1.5928 0.2
1.4109 17.0 459 1.5893 0.2
1.3754 18.0 486 1.5859 0.2
1.385 19.0 513 1.5829 0.2222
1.3607 20.0 540 1.5802 0.2222
1.3947 21.0 567 1.5776 0.2222
1.3764 22.0 594 1.5751 0.2222
1.382 23.0 621 1.5731 0.2222
1.3634 24.0 648 1.5711 0.2222
1.3778 25.0 675 1.5692 0.2222
1.3529 26.0 702 1.5678 0.2222
1.3485 27.0 729 1.5662 0.2222
1.3484 28.0 756 1.5647 0.2222
1.3554 29.0 783 1.5635 0.2222
1.3405 30.0 810 1.5624 0.2222
1.3634 31.0 837 1.5613 0.2222
1.3616 32.0 864 1.5602 0.2222
1.3289 33.0 891 1.5595 0.2222
1.3193 34.0 918 1.5588 0.2
1.3621 35.0 945 1.5580 0.2
1.3672 36.0 972 1.5575 0.2
1.3338 37.0 999 1.5569 0.2
1.3491 38.0 1026 1.5563 0.2
1.3543 39.0 1053 1.5559 0.2
1.3395 40.0 1080 1.5555 0.2
1.3385 41.0 1107 1.5553 0.2
1.3225 42.0 1134 1.5550 0.2
1.3557 43.0 1161 1.5547 0.2
1.3413 44.0 1188 1.5546 0.2
1.3386 45.0 1215 1.5544 0.2
1.3204 46.0 1242 1.5543 0.2
1.335 47.0 1269 1.5543 0.2
1.3373 48.0 1296 1.5542 0.2
1.3715 49.0 1323 1.5542 0.2
1.2935 50.0 1350 1.5542 0.2

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