AlaaHussien/weather_classifier

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: 0.1169
• Validation Loss: 0.2788
• Train Accuracy: 0.9206
• Train Precision: 0.9220
• Train Recall: 0.9206
• Train F1: 0.9208
• 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
0.1984	0.2676	0.9250	0.9266	0.9250	0.9244	0
0.1562	0.2494	0.9279	0.9293	0.9279	0.9280	1
0.1384	0.2656	0.9228	0.9238	0.9228	0.9227	2
0.1186	0.2668	0.9243	0.9248	0.9243	0.9238	3
0.1169	0.2788	0.9206	0.9220	0.9206	0.9208	4

Framework versions

• Transformers 4.51.3
• TensorFlow 2.18.0
• Datasets 3.6.0
• Tokenizers 0.21.1