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hushem_1x_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: 1.5785
  • 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
No log 1.0 6 1.7159 0.2222
1.7117 2.0 12 1.7073 0.2222
1.7117 3.0 18 1.6994 0.2222
1.6883 4.0 24 1.6919 0.2222
1.6982 5.0 30 1.6843 0.2222
1.6982 6.0 36 1.6776 0.2222
1.6419 7.0 42 1.6712 0.2222
1.6419 8.0 48 1.6649 0.2222
1.6108 9.0 54 1.6588 0.2222
1.6345 10.0 60 1.6530 0.2222
1.6345 11.0 66 1.6473 0.2222
1.6108 12.0 72 1.6421 0.2222
1.6108 13.0 78 1.6369 0.2
1.6666 14.0 84 1.6323 0.2
1.6138 15.0 90 1.6282 0.2
1.6138 16.0 96 1.6241 0.2
1.5738 17.0 102 1.6203 0.2
1.5738 18.0 108 1.6167 0.2
1.5952 19.0 114 1.6131 0.2
1.555 20.0 120 1.6099 0.2
1.555 21.0 126 1.6070 0.2
1.5267 22.0 132 1.6040 0.2
1.5267 23.0 138 1.6012 0.2
1.5686 24.0 144 1.5988 0.2
1.5444 25.0 150 1.5966 0.2
1.5444 26.0 156 1.5944 0.2
1.544 27.0 162 1.5926 0.2
1.544 28.0 168 1.5907 0.2
1.5375 29.0 174 1.5889 0.2
1.5441 30.0 180 1.5873 0.2
1.5441 31.0 186 1.5857 0.2
1.5614 32.0 192 1.5845 0.2
1.5614 33.0 198 1.5832 0.2
1.5093 34.0 204 1.5821 0.2
1.5478 35.0 210 1.5812 0.2
1.5478 36.0 216 1.5804 0.2
1.5301 37.0 222 1.5798 0.2
1.5301 38.0 228 1.5793 0.2
1.4582 39.0 234 1.5789 0.2
1.5151 40.0 240 1.5786 0.2
1.5151 41.0 246 1.5785 0.2
1.5298 42.0 252 1.5785 0.2
1.5298 43.0 258 1.5785 0.2
1.548 44.0 264 1.5785 0.2
1.5172 45.0 270 1.5785 0.2
1.5172 46.0 276 1.5785 0.2
1.528 47.0 282 1.5785 0.2
1.528 48.0 288 1.5785 0.2
1.4968 49.0 294 1.5785 0.2
1.5413 50.0 300 1.5785 0.2

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