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dental_classification_model_010424_2

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: 0.5837
  • Accuracy: 0.8142

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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.9273 0.99 41 1.9166 0.2281
1.8096 2.0 83 1.7653 0.3716
1.6373 2.99 124 1.5785 0.4486
1.4996 4.0 166 1.4273 0.5060
1.3441 4.99 207 1.2730 0.5891
1.1677 6.0 249 1.1615 0.6254
0.9809 6.99 290 1.1033 0.6254
0.8292 8.0 332 0.9928 0.6873
0.8035 8.99 373 0.8762 0.7402
0.6982 10.0 415 0.8117 0.7341
0.6992 10.99 456 0.7667 0.7749
0.5601 12.0 498 0.7563 0.7568
0.5358 12.99 539 0.7178 0.7749
0.569 14.0 581 0.7356 0.7553
0.4503 14.99 622 0.6535 0.8051
0.4509 16.0 664 0.6755 0.7855
0.5127 16.99 705 0.6431 0.7976
0.425 18.0 747 0.6362 0.8006
0.3968 18.99 788 0.5821 0.8157
0.398 20.0 830 0.6355 0.7900
0.4468 20.99 871 0.5103 0.8323
0.429 22.0 913 0.6056 0.8051
0.3332 22.99 954 0.5681 0.8233
0.3431 24.0 996 0.5186 0.8263
0.3052 24.99 1037 0.5993 0.8036
0.3495 26.0 1079 0.5837 0.8142

Framework versions

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