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End of training
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metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: hushem_1x_deit_tiny_sgd_lr00001_fold2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.13333333333333333

hushem_1x_deit_tiny_sgd_lr00001_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: 1.6351
  • Accuracy: 0.1333

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 1.6407 0.1333
1.6149 2.0 12 1.6404 0.1333
1.6149 3.0 18 1.6401 0.1333
1.588 4.0 24 1.6398 0.1333
1.6243 5.0 30 1.6396 0.1333
1.6243 6.0 36 1.6393 0.1333
1.6041 7.0 42 1.6390 0.1333
1.6041 8.0 48 1.6388 0.1333
1.5784 9.0 54 1.6386 0.1333
1.61 10.0 60 1.6383 0.1333
1.61 11.0 66 1.6381 0.1333
1.5857 12.0 72 1.6379 0.1333
1.5857 13.0 78 1.6377 0.1333
1.6282 14.0 84 1.6375 0.1333
1.5739 15.0 90 1.6373 0.1333
1.5739 16.0 96 1.6372 0.1333
1.5784 17.0 102 1.6370 0.1333
1.5784 18.0 108 1.6368 0.1333
1.6525 19.0 114 1.6367 0.1333
1.5978 20.0 120 1.6365 0.1333
1.5978 21.0 126 1.6364 0.1333
1.6239 22.0 132 1.6362 0.1333
1.6239 23.0 138 1.6361 0.1333
1.581 24.0 144 1.6360 0.1333
1.597 25.0 150 1.6359 0.1333
1.597 26.0 156 1.6358 0.1333
1.5864 27.0 162 1.6357 0.1333
1.5864 28.0 168 1.6356 0.1333
1.6236 29.0 174 1.6355 0.1333
1.6201 30.0 180 1.6354 0.1333
1.6201 31.0 186 1.6354 0.1333
1.6018 32.0 192 1.6353 0.1333
1.6018 33.0 198 1.6352 0.1333
1.5711 34.0 204 1.6352 0.1333
1.6003 35.0 210 1.6352 0.1333
1.6003 36.0 216 1.6351 0.1333
1.5762 37.0 222 1.6351 0.1333
1.5762 38.0 228 1.6351 0.1333
1.5979 39.0 234 1.6351 0.1333
1.6035 40.0 240 1.6351 0.1333
1.6035 41.0 246 1.6351 0.1333
1.5976 42.0 252 1.6351 0.1333
1.5976 43.0 258 1.6351 0.1333
1.5981 44.0 264 1.6351 0.1333
1.5912 45.0 270 1.6351 0.1333
1.5912 46.0 276 1.6351 0.1333
1.5981 47.0 282 1.6351 0.1333
1.5981 48.0 288 1.6351 0.1333
1.6158 49.0 294 1.6351 0.1333
1.593 50.0 300 1.6351 0.1333

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1