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dental_classification_model_010424_1

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5468
  • Accuracy: 0.8293

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.9173 0.99 41 1.9026 0.2825
1.7055 2.0 83 1.6619 0.3882
1.5398 2.99 124 1.5061 0.4849
1.3415 4.0 166 1.3317 0.5801
1.1753 4.99 207 1.2437 0.5876
1.017 6.0 249 1.1052 0.6390
0.8724 6.99 290 0.9521 0.6873
0.8207 8.0 332 0.9114 0.7115
0.7706 8.99 373 0.8574 0.7130
0.6788 10.0 415 0.7974 0.7523
0.63 10.99 456 0.7611 0.7659
0.5633 12.0 498 0.7764 0.7553
0.5581 12.99 539 0.7370 0.7779
0.5117 14.0 581 0.6945 0.7689
0.4933 14.99 622 0.7066 0.7719
0.4787 16.0 664 0.6405 0.8006
0.4169 16.99 705 0.6443 0.8036
0.3756 18.0 747 0.5991 0.8187
0.3629 18.99 788 0.5774 0.8202
0.3719 20.0 830 0.5451 0.8369
0.4216 20.99 871 0.5623 0.8338
0.3739 22.0 913 0.5995 0.8066
0.3096 22.99 954 0.5330 0.8353
0.3002 24.0 996 0.5109 0.8323
0.3372 24.99 1037 0.5468 0.8293

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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F32
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