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hushem_1x_deit_tiny_rms_001_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: 1.2949
  • Accuracy: 0.3556

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: 0.001
  • 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 6.6312 0.2667
4.1013 2.0 12 2.1471 0.2444
4.1013 3.0 18 1.7992 0.2444
1.7936 4.0 24 1.5377 0.2667
1.5908 5.0 30 1.6029 0.2444
1.5908 6.0 36 1.5728 0.2444
1.533 7.0 42 1.6272 0.2444
1.533 8.0 48 1.5192 0.2667
1.4887 9.0 54 1.4382 0.2444
1.4288 10.0 60 1.4387 0.2444
1.4288 11.0 66 1.4770 0.2667
1.422 12.0 72 1.3624 0.2444
1.422 13.0 78 1.4332 0.2667
1.4231 14.0 84 1.4892 0.2444
1.385 15.0 90 1.3102 0.4222
1.385 16.0 96 1.3352 0.3333
1.4799 17.0 102 1.6140 0.3111
1.4799 18.0 108 1.4774 0.2444
1.4126 19.0 114 1.3130 0.3333
1.3511 20.0 120 1.2400 0.4222
1.3511 21.0 126 1.5468 0.2667
1.412 22.0 132 1.4525 0.2667
1.412 23.0 138 1.2484 0.3778
1.3184 24.0 144 1.5741 0.2444
1.3429 25.0 150 1.3487 0.4444
1.3429 26.0 156 1.3203 0.3111
1.2824 27.0 162 1.2257 0.4222
1.2824 28.0 168 1.3520 0.2222
1.2504 29.0 174 1.1717 0.4667
1.235 30.0 180 1.2327 0.3778
1.235 31.0 186 1.3371 0.4
1.2286 32.0 192 1.3224 0.2889
1.2286 33.0 198 1.2295 0.3778
1.168 34.0 204 1.2716 0.3111
1.2345 35.0 210 1.2743 0.3111
1.2345 36.0 216 1.3964 0.3778
1.2057 37.0 222 1.3905 0.3556
1.2057 38.0 228 1.2908 0.3778
1.1197 39.0 234 1.2888 0.3556
1.1518 40.0 240 1.2704 0.4
1.1518 41.0 246 1.3067 0.3556
1.1311 42.0 252 1.2949 0.3556
1.1311 43.0 258 1.2949 0.3556
1.109 44.0 264 1.2949 0.3556
1.1464 45.0 270 1.2949 0.3556
1.1464 46.0 276 1.2949 0.3556
1.0982 47.0 282 1.2949 0.3556
1.0982 48.0 288 1.2949 0.3556
1.1635 49.0 294 1.2949 0.3556
1.1115 50.0 300 1.2949 0.3556

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