AlaaHussien/final_weather

This model is a fine-tuned version of 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