--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_keras_callback model-index: - name: srikrishnateja/vit-base-patch16-224-in21k-euroSat results: [] --- # srikrishnateja/vit-base-patch16-224-in21k-euroSat 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: 0.0403 - Train Accuracy: 0.9952 - Train Top-3-accuracy: 1.0 - Validation Loss: 0.1351 - Validation Accuracy: 0.9645 - Validation Top-3-accuracy: 1.0 - Epoch: 4 ## 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': 425, '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 | |:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| | 0.4326 | 0.8143 | 1.0 | 0.2613 | 0.9102 | 1.0 | 0 | | 0.1770 | 0.9413 | 1.0 | 0.1919 | 0.9332 | 1.0 | 1 | | 0.0943 | 0.9760 | 1.0 | 0.1654 | 0.9436 | 1.0 | 2 | | 0.0576 | 0.9863 | 1.0 | 0.1457 | 0.9520 | 1.0 | 3 | | 0.0403 | 0.9952 | 1.0 | 0.1351 | 0.9645 | 1.0 | 4 | ### Framework versions - Transformers 4.38.1 - TensorFlow 2.15.0 - Datasets 2.17.1 - Tokenizers 0.15.1