Remunata/rupiah_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: 0.1165
• Train Accuracy: 0.9065
• Validation Loss: 0.4728
• Validation Accuracy: 0.9065
• Epoch: 14

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': 70950, '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
1.0522	0.8485	0.6303	0.8485	0
0.3967	0.8838	0.4676	0.8838	1
0.2908	0.8956	0.4541	0.8956	2
0.2311	0.8675	0.5276	0.8675	3
0.1810	0.8956	0.4133	0.8956	4
0.1782	0.8929	0.4567	0.8929	5
0.1617	0.8730	0.5800	0.8730	6
0.1442	0.9047	0.4201	0.9047	7
0.1471	0.9102	0.4024	0.9102	8
0.1149	0.9093	0.4297	0.9093	9
0.1198	0.9056	0.4753	0.9056	10
0.1132	0.9056	0.4562	0.9056	11
0.1132	0.9102	0.3935	0.9102	12
0.1015	0.9056	0.4687	0.9056	13
0.1165	0.9065	0.4728	0.9065	14

Framework versions

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