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hushem_1x_deit_small_adamax_0001_fold2

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

  • Loss: 2.0748
  • Accuracy: 0.6

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
No log 1.0 6 1.2729 0.4
1.2121 2.0 12 1.1250 0.6222
1.2121 3.0 18 1.2362 0.5556
0.4291 4.0 24 1.2042 0.6444
0.1116 5.0 30 1.1861 0.6
0.1116 6.0 36 1.6632 0.5556
0.0196 7.0 42 1.7499 0.6
0.0196 8.0 48 1.7915 0.5556
0.0051 9.0 54 1.8168 0.5778
0.0016 10.0 60 1.8187 0.6222
0.0016 11.0 66 1.8480 0.6222
0.0008 12.0 72 1.8621 0.6222
0.0008 13.0 78 1.8730 0.6222
0.0006 14.0 84 1.8908 0.6222
0.0005 15.0 90 1.9136 0.6222
0.0005 16.0 96 1.9335 0.6222
0.0004 17.0 102 1.9501 0.6222
0.0004 18.0 108 1.9655 0.6222
0.0004 19.0 114 1.9783 0.6222
0.0003 20.0 120 1.9900 0.6222
0.0003 21.0 126 1.9990 0.6222
0.0003 22.0 132 2.0067 0.6222
0.0003 23.0 138 2.0139 0.6
0.0003 24.0 144 2.0208 0.6
0.0003 25.0 150 2.0271 0.6
0.0003 26.0 156 2.0322 0.6
0.0003 27.0 162 2.0367 0.6
0.0003 28.0 168 2.0419 0.6
0.0003 29.0 174 2.0471 0.6
0.0003 30.0 180 2.0520 0.6
0.0003 31.0 186 2.0560 0.6
0.0002 32.0 192 2.0593 0.6
0.0002 33.0 198 2.0621 0.6
0.0003 34.0 204 2.0649 0.6
0.0003 35.0 210 2.0672 0.6
0.0003 36.0 216 2.0692 0.6
0.0002 37.0 222 2.0710 0.6
0.0002 38.0 228 2.0723 0.6
0.0002 39.0 234 2.0735 0.6
0.0002 40.0 240 2.0742 0.6
0.0002 41.0 246 2.0747 0.6
0.0002 42.0 252 2.0748 0.6
0.0002 43.0 258 2.0748 0.6
0.0002 44.0 264 2.0748 0.6
0.0002 45.0 270 2.0748 0.6
0.0002 46.0 276 2.0748 0.6
0.0002 47.0 282 2.0748 0.6
0.0002 48.0 288 2.0748 0.6
0.0002 49.0 294 2.0748 0.6
0.0002 50.0 300 2.0748 0.6

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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Evaluation results