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hushem_5x_deit_base_rms_0001_fold2

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: 5.1764
  • Accuracy: 0.5333

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
1.4732 1.0 27 1.5871 0.2667
1.4137 2.0 54 1.4271 0.2667
1.462 3.0 81 1.4098 0.2667
1.4423 4.0 108 1.4316 0.2444
1.4677 5.0 135 1.1736 0.6
1.1753 6.0 162 1.3090 0.4889
1.0628 7.0 189 1.1008 0.4
0.8856 8.0 216 1.3194 0.4667
0.7266 9.0 243 1.5517 0.4667
0.7206 10.0 270 1.5964 0.4222
0.6825 11.0 297 1.9511 0.5333
0.6024 12.0 324 1.1289 0.5111
0.7093 13.0 351 1.6051 0.4667
0.5446 14.0 378 1.0604 0.5333
0.4716 15.0 405 2.6293 0.5778
0.4728 16.0 432 3.2908 0.4889
0.5099 17.0 459 2.0246 0.5333
0.4809 18.0 486 3.4545 0.5333
0.3484 19.0 513 2.2451 0.5111
0.352 20.0 540 2.8572 0.4889
0.3258 21.0 567 3.5970 0.5556
0.2785 22.0 594 3.6404 0.5556
0.3005 23.0 621 3.6333 0.5111
0.2089 24.0 648 4.2561 0.5333
0.1996 25.0 675 3.8526 0.5111
0.1044 26.0 702 4.1245 0.5333
0.2042 27.0 729 3.9154 0.5556
0.1371 28.0 756 3.3906 0.5556
0.1014 29.0 783 4.2534 0.5556
0.0761 30.0 810 3.8328 0.5778
0.0321 31.0 837 4.5117 0.5556
0.1194 32.0 864 4.5296 0.5333
0.0072 33.0 891 4.9299 0.5333
0.0276 34.0 918 5.0433 0.5111
0.0121 35.0 945 4.9519 0.5333
0.0051 36.0 972 4.9546 0.5333
0.0001 37.0 999 4.9700 0.5111
0.0001 38.0 1026 4.9962 0.5111
0.0 39.0 1053 5.0319 0.5111
0.0 40.0 1080 5.0566 0.5111
0.0001 41.0 1107 5.0812 0.5333
0.0 42.0 1134 5.1051 0.5333
0.0 43.0 1161 5.1228 0.5333
0.0 44.0 1188 5.1393 0.5333
0.0 45.0 1215 5.1531 0.5333
0.0 46.0 1242 5.1647 0.5333
0.0 47.0 1269 5.1724 0.5333
0.0 48.0 1296 5.1763 0.5333
0.0 49.0 1323 5.1764 0.5333
0.0 50.0 1350 5.1764 0.5333

Framework versions

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