Remunata/rupiah_classifier_v2

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: 0.1314
• Train Accuracy: 0.9379
• Validation Loss: 0.2477
• Validation Accuracy: 0.9379
• Epoch: 9

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': 66500, '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	Validation Loss	Validation Accuracy	Epoch
0.9566	0.8213	0.6179	0.8213	0
0.3346	0.8828	0.4223	0.8828	1
0.2572	0.9048	0.3674	0.9048	2
0.2092	0.9181	0.3146	0.9181	3
0.1856	0.9112	0.3320	0.9112	4
0.1722	0.8999	0.4168	0.8999	5
0.1564	0.9406	0.2184	0.9406	6
0.1402	0.8935	0.4184	0.8935	7
0.1352	0.9230	0.2832	0.9230	8
0.1314	0.9379	0.2477	0.9379	9

Framework versions

• Transformers 4.41.2
• TensorFlow 2.15.0
• Datasets 2.19.2
• Tokenizers 0.19.1