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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_0001_fold1
    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: 0.3333333333333333

hushem_1x_deit_tiny_sgd_0001_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: 1.5492
  • Accuracy: 0.3333

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
No log 1.0 6 1.6732 0.2667
1.7181 2.0 12 1.6650 0.2667
1.7181 3.0 18 1.6576 0.2667
1.6899 4.0 24 1.6505 0.2667
1.7151 5.0 30 1.6435 0.2889
1.7151 6.0 36 1.6372 0.2889
1.6507 7.0 42 1.6312 0.2889
1.6507 8.0 48 1.6255 0.2889
1.626 9.0 54 1.6199 0.2889
1.6566 10.0 60 1.6145 0.2889
1.6566 11.0 66 1.6095 0.2889
1.6122 12.0 72 1.6048 0.2889
1.6122 13.0 78 1.6001 0.2889
1.7016 14.0 84 1.5960 0.2889
1.6075 15.0 90 1.5922 0.2889
1.6075 16.0 96 1.5886 0.2889
1.5839 17.0 102 1.5852 0.2889
1.5839 18.0 108 1.5821 0.3111
1.589 19.0 114 1.5790 0.3111
1.5539 20.0 120 1.5762 0.3111
1.5539 21.0 126 1.5736 0.3111
1.5431 22.0 132 1.5710 0.3111
1.5431 23.0 138 1.5686 0.3111
1.58 24.0 144 1.5665 0.3111
1.5398 25.0 150 1.5646 0.3333
1.5398 26.0 156 1.5627 0.3333
1.5415 27.0 162 1.5611 0.3333
1.5415 28.0 168 1.5596 0.3333
1.5548 29.0 174 1.5581 0.3333
1.5423 30.0 180 1.5567 0.3333
1.5423 31.0 186 1.5553 0.3333
1.5803 32.0 192 1.5542 0.3333
1.5803 33.0 198 1.5532 0.3333
1.4986 34.0 204 1.5522 0.3333
1.5635 35.0 210 1.5514 0.3333
1.5635 36.0 216 1.5508 0.3333
1.5318 37.0 222 1.5503 0.3333
1.5318 38.0 228 1.5499 0.3333
1.4575 39.0 234 1.5495 0.3333
1.527 40.0 240 1.5493 0.3333
1.527 41.0 246 1.5492 0.3333
1.5482 42.0 252 1.5492 0.3333
1.5482 43.0 258 1.5492 0.3333
1.5545 44.0 264 1.5492 0.3333
1.5122 45.0 270 1.5492 0.3333
1.5122 46.0 276 1.5492 0.3333
1.5284 47.0 282 1.5492 0.3333
1.5284 48.0 288 1.5492 0.3333
1.5117 49.0 294 1.5492 0.3333
1.5484 50.0 300 1.5492 0.3333

Framework versions

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