Imene/vit-base-patch16-224-in21k-wi2

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: 2.9892
• Train Accuracy: 0.5568
• Train Top-3-accuracy: 0.8130
• Validation Loss: 3.0923
• Validation Accuracy: 0.4280
• Validation Top-3-accuracy: 0.7034
• 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': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, '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
3.8488	0.0720	0.1713	3.7116	0.1564	0.3617	0
3.5246	0.2703	0.4898	3.4122	0.3217	0.5732	1
3.2493	0.4150	0.6827	3.2232	0.3880	0.6633	2
3.0840	0.5002	0.7670	3.1275	0.4255	0.6921	3
2.9892	0.5568	0.8130	3.0923	0.4280	0.7034	4

Framework versions

• Transformers 4.21.3
• TensorFlow 2.8.2
• Datasets 2.4.0
• Tokenizers 0.12.1