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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
  - generated_from_keras_callback
model-index:
  - name: vit-base-patch16-224-5class224
    results: []

vit-base-patch16-224-5class224

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

  • Train Loss: 0.0115
  • Train Accuracy: 0.9460
  • Train Top-3-accuracy: 0.9911
  • Validation Loss: 0.1621
  • Validation Accuracy: 0.9490
  • Validation Top-3-accuracy: 0.9916
  • Epoch: 6

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: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 574, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Train Accuracy Train Top-3-accuracy Validation Loss Validation Accuracy Validation Top-3-accuracy Epoch
0.7725 0.6414 0.8898 0.3755 0.7636 0.9478 0
0.2160 0.8219 0.9635 0.2372 0.8557 0.9726 1
0.0696 0.8812 0.9780 0.2035 0.8989 0.9818 2
0.0344 0.9108 0.9842 0.1715 0.9203 0.9860 3
0.0194 0.9278 0.9875 0.1911 0.9337 0.9888 4
0.0147 0.9381 0.9897 0.1651 0.9425 0.9904 5
0.0115 0.9460 0.9911 0.1621 0.9490 0.9916 6

Framework versions

  • Transformers 4.41.2
  • TensorFlow 2.15.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1