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XO-Appleton/vit-base-patch16-224-in21k-MR

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: 0.0042
  • Train Accuracy: 1.0
  • Train Top-3-accuracy: 1.0
  • Validation Loss: 0.0126
  • Validation Accuracy: 0.9983
  • Validation Top-3-accuracy: 1.0
  • Epoch: 3

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': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 4485, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, '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
0.1624 0.9544 1.0 0.0380 0.9933 1.0 0
0.0178 0.9979 1.0 0.0197 0.9966 1.0 1
0.0063 1.0 1.0 0.0139 0.9983 1.0 2
0.0042 1.0 1.0 0.0126 0.9983 1.0 3

Framework versions

  • Transformers 4.30.2
  • TensorFlow 2.12.0
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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