traynothein_resize_treeclasss

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: 0.0426
• Train Accuracy: 0.9814
• Train Top-3-accuracy: 1.0
• Validation Loss: 0.0803
• Validation Accuracy: 0.9823
• Validation Top-3-accuracy: 1.0
• Epoch: 6

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': 504, '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	Train Accuracy	Train Top-3-accuracy	Validation Loss	Validation Accuracy	Validation Top-3-accuracy	Epoch
0.4021	0.8416	1.0	0.1892	0.9342	1.0	0
0.1232	0.9479	1.0	0.1078	0.9574	1.0	1
0.0852	0.9635	1.0	0.1014	0.9678	1.0	2
0.0597	0.9712	1.0	0.0798	0.9740	1.0	3
0.0549	0.9761	1.0	0.0891	0.9777	1.0	4
0.0485	0.9790	1.0	0.0754	0.9803	1.0	5
0.0426	0.9814	1.0	0.0803	0.9823	1.0	6

Framework versions

• Transformers 4.44.2
• TensorFlow 2.15.1
• Datasets 3.0.0
• Tokenizers 0.19.1