traynothein_resize_foreclasss

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: 0.0744
• Train Accuracy: 0.9404
• Train Top-3-accuracy: 0.9991
• Validation Loss: 0.2720
• Validation Accuracy: 0.9431
• Validation Top-3-accuracy: 0.9991
• 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': 658, '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
0.6708	0.7378	0.9752	0.4218	0.8246	0.9933	0
0.3109	0.8569	0.9956	0.3083	0.8754	0.9968	1
0.2024	0.8899	0.9975	0.2776	0.9011	0.9979	2
0.1370	0.9104	0.9982	0.2734	0.9170	0.9985	3
0.0996	0.9237	0.9986	0.2775	0.9288	0.9988	4
0.0814	0.9334	0.9989	0.2695	0.9372	0.9990	5
0.0744	0.9404	0.9991	0.2720	0.9431	0.9991	6

Framework versions

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