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hushem_1x_deit_base_sgd_001_fold4

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

  • Loss: 1.3500
  • Accuracy: 0.3571

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 1.4099 0.1667
1.4464 2.0 12 1.4056 0.1667
1.4464 3.0 18 1.4012 0.1667
1.409 4.0 24 1.3971 0.1667
1.405 5.0 30 1.3937 0.1905
1.405 6.0 36 1.3906 0.1905
1.3913 7.0 42 1.3880 0.1905
1.3913 8.0 48 1.3852 0.1905
1.3821 9.0 54 1.3824 0.1667
1.3709 10.0 60 1.3801 0.1667
1.3709 11.0 66 1.3778 0.1905
1.3643 12.0 72 1.3757 0.2143
1.3643 13.0 78 1.3738 0.2619
1.3452 14.0 84 1.3719 0.2619
1.3451 15.0 90 1.3702 0.2619
1.3451 16.0 96 1.3686 0.2619
1.3306 17.0 102 1.3669 0.2619
1.3306 18.0 108 1.3655 0.2857
1.3266 19.0 114 1.3643 0.2857
1.3291 20.0 120 1.3632 0.2857
1.3291 21.0 126 1.3620 0.2857
1.3218 22.0 132 1.3610 0.2857
1.3218 23.0 138 1.3598 0.3095
1.3151 24.0 144 1.3588 0.3333
1.3182 25.0 150 1.3578 0.3333
1.3182 26.0 156 1.3568 0.3333
1.3072 27.0 162 1.3559 0.3333
1.3072 28.0 168 1.3552 0.3333
1.3081 29.0 174 1.3545 0.3571
1.3087 30.0 180 1.3539 0.3571
1.3087 31.0 186 1.3532 0.3571
1.2983 32.0 192 1.3527 0.3571
1.2983 33.0 198 1.3521 0.3333
1.2931 34.0 204 1.3516 0.3571
1.2999 35.0 210 1.3512 0.3571
1.2999 36.0 216 1.3509 0.3571
1.2926 37.0 222 1.3506 0.3571
1.2926 38.0 228 1.3504 0.3571
1.2948 39.0 234 1.3502 0.3571
1.2828 40.0 240 1.3501 0.3571
1.2828 41.0 246 1.3500 0.3571
1.2878 42.0 252 1.3500 0.3571
1.2878 43.0 258 1.3500 0.3571
1.2878 44.0 264 1.3500 0.3571
1.2935 45.0 270 1.3500 0.3571
1.2935 46.0 276 1.3500 0.3571
1.289 47.0 282 1.3500 0.3571
1.289 48.0 288 1.3500 0.3571
1.2878 49.0 294 1.3500 0.3571
1.2975 50.0 300 1.3500 0.3571

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.7
  • Tokenizers 0.15.0
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Evaluation results