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hushem_1x_beit_base_sgd_0001_fold3

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: 1.5102
  • Accuracy: 0.2326

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 1.5815 0.2558
1.5795 2.0 12 1.5768 0.2558
1.5795 3.0 18 1.5725 0.2558
1.5843 4.0 24 1.5685 0.2558
1.5064 5.0 30 1.5650 0.2558
1.5064 6.0 36 1.5613 0.2558
1.5264 7.0 42 1.5577 0.2558
1.5264 8.0 48 1.5544 0.2558
1.5341 9.0 54 1.5511 0.2558
1.5468 10.0 60 1.5482 0.2558
1.5468 11.0 66 1.5458 0.2558
1.5265 12.0 72 1.5432 0.2558
1.5265 13.0 78 1.5409 0.2558
1.4949 14.0 84 1.5386 0.2558
1.5252 15.0 90 1.5362 0.2558
1.5252 16.0 96 1.5341 0.2558
1.5295 17.0 102 1.5321 0.2558
1.5295 18.0 108 1.5302 0.2558
1.4916 19.0 114 1.5284 0.2558
1.4984 20.0 120 1.5267 0.2326
1.4984 21.0 126 1.5250 0.2326
1.5211 22.0 132 1.5235 0.2326
1.5211 23.0 138 1.5222 0.2326
1.506 24.0 144 1.5209 0.2326
1.483 25.0 150 1.5197 0.2326
1.483 26.0 156 1.5185 0.2326
1.5184 27.0 162 1.5173 0.2326
1.5184 28.0 168 1.5163 0.2326
1.536 29.0 174 1.5154 0.2326
1.4949 30.0 180 1.5146 0.2326
1.4949 31.0 186 1.5138 0.2326
1.5188 32.0 192 1.5132 0.2326
1.5188 33.0 198 1.5126 0.2326
1.4387 34.0 204 1.5120 0.2326
1.4953 35.0 210 1.5116 0.2326
1.4953 36.0 216 1.5112 0.2326
1.4703 37.0 222 1.5108 0.2326
1.4703 38.0 228 1.5106 0.2326
1.5017 39.0 234 1.5104 0.2326
1.4757 40.0 240 1.5103 0.2326
1.4757 41.0 246 1.5102 0.2326
1.4714 42.0 252 1.5102 0.2326
1.4714 43.0 258 1.5102 0.2326
1.4776 44.0 264 1.5102 0.2326
1.4921 45.0 270 1.5102 0.2326
1.4921 46.0 276 1.5102 0.2326
1.4896 47.0 282 1.5102 0.2326
1.4896 48.0 288 1.5102 0.2326
1.4789 49.0 294 1.5102 0.2326
1.4671 50.0 300 1.5102 0.2326

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Finetuned from

Evaluation results