--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_keras_callback model-index: - name: dwiedarioo/vit-base-patch16-224-in21k-final2multibrainmri results: [] --- # dwiedarioo/vit-base-patch16-224-in21k-final2multibrainmri This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0516 - Train Accuracy: 1.0 - Train Top-3-accuracy: 1.0 - Validation Loss: 0.1325 - Validation Accuracy: 0.9784 - Validation Top-3-accuracy: 0.9957 - Epoch: 17 ## 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': 8200, '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 | |:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| | 2.2742 | 0.3856 | 0.6522 | 1.8596 | 0.6112 | 0.8337 | 0 | | 1.5673 | 0.6919 | 0.8778 | 1.3120 | 0.7883 | 0.9136 | 1 | | 1.0377 | 0.8622 | 0.9576 | 0.9078 | 0.8661 | 0.9611 | 2 | | 0.6816 | 0.9511 | 0.9859 | 0.6497 | 0.9222 | 0.9849 | 3 | | 0.4698 | 0.9805 | 0.9939 | 0.5104 | 0.9395 | 0.9870 | 4 | | 0.3375 | 0.9897 | 0.9973 | 0.3975 | 0.9590 | 0.9892 | 5 | | 0.2554 | 0.9966 | 0.9992 | 0.3107 | 0.9676 | 0.9978 | 6 | | 0.2346 | 0.9905 | 0.9992 | 0.3804 | 0.9287 | 0.9914 | 7 | | 0.1976 | 0.9935 | 0.9989 | 0.3250 | 0.9546 | 0.9914 | 8 | | 0.1686 | 0.9939 | 0.9992 | 0.4980 | 0.8920 | 0.9762 | 9 | | 0.1423 | 0.9969 | 0.9996 | 0.2129 | 0.9654 | 0.9957 | 10 | | 0.1073 | 0.9992 | 1.0 | 0.1840 | 0.9741 | 0.9978 | 11 | | 0.0925 | 0.9992 | 1.0 | 0.1714 | 0.9719 | 0.9978 | 12 | | 0.0809 | 0.9992 | 1.0 | 0.1595 | 0.9719 | 0.9978 | 13 | | 0.0715 | 0.9992 | 1.0 | 0.1503 | 0.9719 | 0.9978 | 14 | | 0.0637 | 1.0 | 1.0 | 0.1426 | 0.9762 | 0.9978 | 15 | | 0.0573 | 0.9996 | 1.0 | 0.1361 | 0.9784 | 0.9978 | 16 | | 0.0516 | 1.0 | 1.0 | 0.1325 | 0.9784 | 0.9957 | 17 | ### Framework versions - Transformers 4.35.0 - TensorFlow 2.14.0 - Datasets 2.14.6 - Tokenizers 0.14.1