hushem_1x_beit_base_adamax_0001_fold2

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

  • Loss: 1.0153
  • Accuracy: 0.8

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 1.2331 0.5556
1.3348 2.0 12 0.8218 0.6889
1.3348 3.0 18 0.6484 0.7556
0.3555 4.0 24 0.8513 0.7556
0.1239 5.0 30 0.7326 0.7333
0.1239 6.0 36 0.6190 0.8
0.0625 7.0 42 1.0407 0.7333
0.0625 8.0 48 0.7902 0.8
0.0045 9.0 54 0.8103 0.7778
0.0021 10.0 60 1.0314 0.8
0.0021 11.0 66 1.1219 0.7556
0.0013 12.0 72 1.0834 0.7556
0.0013 13.0 78 1.0270 0.7333
0.0006 14.0 84 1.0518 0.7556
0.0005 15.0 90 1.0755 0.7556
0.0005 16.0 96 1.1073 0.7556
0.0005 17.0 102 1.1726 0.7556
0.0005 18.0 108 1.2002 0.7556
0.0005 19.0 114 1.1838 0.7556
0.0007 20.0 120 1.1860 0.7556
0.0007 21.0 126 1.2997 0.7556
0.0003 22.0 132 1.3311 0.7556
0.0003 23.0 138 1.3197 0.7556
0.0002 24.0 144 1.2630 0.7556
0.0003 25.0 150 1.1925 0.7556
0.0003 26.0 156 1.1444 0.7778
0.0002 27.0 162 1.1105 0.7778
0.0002 28.0 168 1.0790 0.7778
0.0002 29.0 174 1.0616 0.7778
0.0002 30.0 180 1.0495 0.7778
0.0002 31.0 186 1.0431 0.7778
0.0002 32.0 192 1.0407 0.7778
0.0002 33.0 198 1.0375 0.8
0.0107 34.0 204 1.0331 0.8
0.0002 35.0 210 1.0311 0.8
0.0002 36.0 216 1.0289 0.8
0.0002 37.0 222 1.0264 0.8
0.0002 38.0 228 1.0203 0.8
0.0003 39.0 234 1.0167 0.8
0.0002 40.0 240 1.0146 0.8
0.0002 41.0 246 1.0152 0.8
0.0002 42.0 252 1.0153 0.8
0.0002 43.0 258 1.0153 0.8
0.0002 44.0 264 1.0153 0.8
0.0002 45.0 270 1.0153 0.8
0.0002 46.0 276 1.0153 0.8
0.002 47.0 282 1.0153 0.8
0.002 48.0 288 1.0153 0.8
0.0006 49.0 294 1.0153 0.8
0.0001 50.0 300 1.0153 0.8

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