--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_keras_callback model-index: - name: AlaaHussien/final_weather results: [] --- # AlaaHussien/final_weather 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: 0.1179 - Validation Loss: 0.2876 - Train Accuracy: 0.9235 - Train Precision: 0.9249 - Train Recall: 0.9235 - Train F1: 0.9237 - 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: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 27445, '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 | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch | |:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:| | 0.1824 | 0.3373 | 0.9039 | 0.9071 | 0.9039 | 0.9041 | 0 | | 0.1671 | 0.2880 | 0.9133 | 0.9159 | 0.9133 | 0.9132 | 1 | | 0.1320 | 0.3227 | 0.9126 | 0.9149 | 0.9126 | 0.9127 | 2 | | 0.1241 | 0.2833 | 0.9199 | 0.9223 | 0.9199 | 0.9200 | 3 | | 0.1179 | 0.2876 | 0.9235 | 0.9249 | 0.9235 | 0.9237 | 4 | ### Framework versions - Transformers 4.51.3 - TensorFlow 2.18.0 - Datasets 3.6.0 - Tokenizers 0.21.1