srikrishnateja/vit-cctv

srikrishnateja/vit-base-patch16-224-in21k-euroSat

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: 0.0403
• 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