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hushem_1x_deit_tiny_sgd_00001_fold5

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: 1.7419
  • Accuracy: 0.2439

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: 1e-05
  • 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 1.7664 0.2439
1.7149 2.0 12 1.7652 0.2439
1.7149 3.0 18 1.7640 0.2439
1.7055 4.0 24 1.7627 0.2439
1.7032 5.0 30 1.7616 0.2439
1.7032 6.0 36 1.7604 0.2439
1.7195 7.0 42 1.7594 0.2439
1.7195 8.0 48 1.7584 0.2439
1.6458 9.0 54 1.7574 0.2439
1.7017 10.0 60 1.7564 0.2439
1.7017 11.0 66 1.7554 0.2439
1.7123 12.0 72 1.7545 0.2439
1.7123 13.0 78 1.7536 0.2439
1.6713 14.0 84 1.7528 0.2439
1.6849 15.0 90 1.7520 0.2439
1.6849 16.0 96 1.7512 0.2439
1.7051 17.0 102 1.7505 0.2439
1.7051 18.0 108 1.7498 0.2439
1.6541 19.0 114 1.7491 0.2439
1.7161 20.0 120 1.7484 0.2439
1.7161 21.0 126 1.7478 0.2439
1.6901 22.0 132 1.7472 0.2439
1.6901 23.0 138 1.7466 0.2439
1.6528 24.0 144 1.7461 0.2439
1.7234 25.0 150 1.7456 0.2439
1.7234 26.0 156 1.7451 0.2439
1.6839 27.0 162 1.7447 0.2439
1.6839 28.0 168 1.7443 0.2439
1.6859 29.0 174 1.7439 0.2439
1.6955 30.0 180 1.7436 0.2439
1.6955 31.0 186 1.7433 0.2439
1.7014 32.0 192 1.7430 0.2439
1.7014 33.0 198 1.7428 0.2439
1.6319 34.0 204 1.7426 0.2439
1.6586 35.0 210 1.7424 0.2439
1.6586 36.0 216 1.7422 0.2439
1.6897 37.0 222 1.7421 0.2439
1.6897 38.0 228 1.7420 0.2439
1.6863 39.0 234 1.7420 0.2439
1.6801 40.0 240 1.7419 0.2439
1.6801 41.0 246 1.7419 0.2439
1.7183 42.0 252 1.7419 0.2439
1.7183 43.0 258 1.7419 0.2439
1.6529 44.0 264 1.7419 0.2439
1.6913 45.0 270 1.7419 0.2439
1.6913 46.0 276 1.7419 0.2439
1.7139 47.0 282 1.7419 0.2439
1.7139 48.0 288 1.7419 0.2439
1.6464 49.0 294 1.7419 0.2439
1.6966 50.0 300 1.7419 0.2439

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