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adhisetiawan/
mnist-test

Name: mnist-test
Availability: InStock

transformers

vit

image-classification

generated_from_keras_callback

google/vit-base-patch16-224-in21k

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adhisetiawan/mnist-test

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: 0.7312
Validation Loss: 0.9257
Train Accuracy: 0.8
Epoch: 19

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': 1600, '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	Validation Loss	Train Accuracy	Epoch
2.2668	2.2081	0.4	0
2.1502	2.1140	0.6	1
2.0506	2.0350	0.65	2
1.9473	1.9239	0.7	3
1.8164	1.8355	0.7	4
1.7091	1.7534	0.75	5
1.6152	1.6683	0.8	6
1.5122	1.5825	0.8	7
1.4108	1.4897	0.8	8
1.3225	1.4149	0.8	9
1.2426	1.3135	0.8	10
1.1740	1.2704	0.8	11
1.0894	1.2213	0.85	12
1.0230	1.1424	0.8	13
0.9646	1.1171	0.85	14
0.9109	1.0744	0.8	15
0.8547	1.0376	0.85	16
0.8082	0.9892	0.8	17
0.7632	0.9604	0.85	18
0.7312	0.9257	0.8	19

Framework versions

Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.16.1
Tokenizers 0.15.0