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hushem_1x_deit_tiny_sgd_00001_fold1

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: 1.6938
  • Accuracy: 0.2

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 1.6986 0.2
1.6333 2.0 12 1.6983 0.2
1.6333 3.0 18 1.6981 0.2
1.6088 4.0 24 1.6979 0.2
1.6296 5.0 30 1.6976 0.2
1.6296 6.0 36 1.6974 0.2
1.6252 7.0 42 1.6972 0.2
1.6252 8.0 48 1.6970 0.2
1.6833 9.0 54 1.6968 0.2
1.5983 10.0 60 1.6965 0.2
1.5983 11.0 66 1.6964 0.2
1.61 12.0 72 1.6962 0.2
1.61 13.0 78 1.6960 0.2
1.6125 14.0 84 1.6958 0.2
1.6595 15.0 90 1.6957 0.2
1.6595 16.0 96 1.6956 0.2
1.6372 17.0 102 1.6954 0.2
1.6372 18.0 108 1.6953 0.2
1.6292 19.0 114 1.6951 0.2
1.6414 20.0 120 1.6950 0.2
1.6414 21.0 126 1.6949 0.2
1.6168 22.0 132 1.6948 0.2
1.6168 23.0 138 1.6947 0.2
1.6445 24.0 144 1.6946 0.2
1.6172 25.0 150 1.6945 0.2
1.6172 26.0 156 1.6944 0.2
1.5925 27.0 162 1.6944 0.2
1.5925 28.0 168 1.6943 0.2
1.6351 29.0 174 1.6942 0.2
1.6161 30.0 180 1.6941 0.2
1.6161 31.0 186 1.6941 0.2
1.6095 32.0 192 1.6940 0.2
1.6095 33.0 198 1.6940 0.2
1.6215 34.0 204 1.6939 0.2
1.6213 35.0 210 1.6939 0.2
1.6213 36.0 216 1.6939 0.2
1.6372 37.0 222 1.6938 0.2
1.6372 38.0 228 1.6938 0.2
1.6199 39.0 234 1.6938 0.2
1.6087 40.0 240 1.6938 0.2
1.6087 41.0 246 1.6938 0.2
1.6309 42.0 252 1.6938 0.2
1.6309 43.0 258 1.6938 0.2
1.6203 44.0 264 1.6938 0.2
1.6564 45.0 270 1.6938 0.2
1.6564 46.0 276 1.6938 0.2
1.6178 47.0 282 1.6938 0.2
1.6178 48.0 288 1.6938 0.2
1.6557 49.0 294 1.6938 0.2
1.6181 50.0 300 1.6938 0.2

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