dwiedarioo/vit-base-patch16-224-in21k-brainmri

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:

  • Train Loss: 0.2848
  • Train Accuracy: 0.9969
  • Train Top-3-accuracy: 0.9992
  • Validation Loss: 0.3786
  • Validation Accuracy: 0.9590
  • Validation Top-3-accuracy: 0.9892
  • Epoch: 7

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:

  • optimizer: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1230, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
  • training_precision: mixed_float16

Training results

Train Loss Train Accuracy Train Top-3-accuracy Validation Loss Validation Accuracy Validation Top-3-accuracy Epoch
2.2199 0.4215 0.6564 1.8634 0.5702 0.8099 0
1.5448 0.6976 0.8797 1.3110 0.7603 0.9028 1
1.0494 0.8694 0.9519 0.9507 0.8855 0.9590 2
0.7408 0.9381 0.9824 0.7499 0.9114 0.9806 3
0.5428 0.9756 0.9939 0.5831 0.9460 0.9849 4
0.4169 0.9901 0.9977 0.4895 0.9525 0.9914 5
0.3371 0.9947 0.9977 0.4194 0.9611 0.9892 6
0.2848 0.9969 0.9992 0.3786 0.9590 0.9892 7

Framework versions

  • Transformers 4.35.0
  • TensorFlow 2.14.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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