readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: Imene/vit-base-patch16-384-wi4
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # Imene/vit-base-patch16-384-wi4
  
  This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.1742
  - Train Accuracy: 0.9982
  - Train Top-3-accuracy: 0.9997
  - Validation Loss: 1.5010
  - Validation Accuracy: 0.5746
  - Validation Top-3-accuracy: 0.8040
  - Epoch: 10
  
  ## 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': 1800, '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 |
  |:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
  | 3.7777     | 0.0845         | 0.1855               | 3.3754          | 0.1543              | 0.3014                    | 0     |
  | 2.7253     | 0.3277         | 0.5560               | 2.4975          | 0.3452              | 0.5892                    | 1     |
  | 2.0079     | 0.5236         | 0.7589               | 2.1228          | 0.4234              | 0.6882                    | 2     |
  | 1.5256     | 0.6663         | 0.8549               | 1.9117          | 0.4734              | 0.7445                    | 3     |
  | 1.1602     | 0.7712         | 0.9270               | 1.8059          | 0.5162              | 0.7560                    | 4     |
  | 0.8509     | 0.8659         | 0.9614               | 1.6534          | 0.5516              | 0.7758                    | 5     |
  | 0.5955     | 0.9353         | 0.9836               | 1.6139          | 0.5610              | 0.7935                    | 6     |
  | 0.4229     | 0.9687         | 0.9940               | 1.5655          | 0.5631              | 0.7925                    | 7     |
  | 0.3045     | 0.9859         | 0.9979               | 1.5290          | 0.5714              | 0.7987                    | 8     |
  | 0.2221     | 0.9958         | 0.9990               | 1.5061          | 0.5954              | 0.8008                    | 9     |
  | 0.1742     | 0.9982         | 0.9997               | 1.5010          | 0.5746              | 0.8040                    | 10    |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - TensorFlow 2.8.2
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  