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akar49/
VIT_braintumor_classifier

Name: VIT_braintumor_classifier
Availability: InStock

transformers

vit

image-classification

generated_from_keras_callback

google/vit-base-patch16-224-in21k

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VIT_braintumor_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: 0.0945
Validation Loss: 1.7241
Train Accuracy: 0.6974
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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': np.float32(0.01), 'momentum': 0.0, 'nesterov': False}
training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.7946	1.1484	0.6272	0
0.3246	1.1792	0.6769	1
0.2266	1.2812	0.6842	2
0.1841	1.5085	0.6754	3
0.1589	1.4224	0.6944	4
0.1244	1.4229	0.6901	5
0.1174	1.4858	0.6784	6
0.1133	1.4221	0.6974	7
0.1026	1.4273	0.7003	8
0.1083	1.5406	0.7003	9
0.1038	1.6223	0.6974	10
0.0876	1.5613	0.6959	11
0.1018	1.4540	0.7149	12
0.0808	1.4853	0.7193	13
0.0945	1.7241	0.6974	14

Framework versions

Transformers 4.52.4
TensorFlow 2.18.0
Datasets 3.6.0
Tokenizers 0.21.1

akar49/VIT_braintumor_classifier

VIT_braintumor_classifier

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

akar49/
VIT_braintumor_classifier