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codingwithboba/
cifar_classifier

Name: cifar_classifier
Rating: 2.5 (5 reviews)

transformers

vit

image-classification

generated_from_keras_callback

apache-2.0

autotrain_compatible

endpoints_compatible

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codingwithboba/cifar_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: 0.1524
Validation Loss: 0.3447
Train Accuracy: 0.902
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: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 20000, '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}
training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
1.6641	0.9964	0.825	0
0.7272	0.5292	0.904	1
0.3683	0.4030	0.895	2
0.2274	0.3136	0.924	3
0.1524	0.3447	0.902	4

Framework versions

Transformers 4.29.1
TensorFlow 2.12.0
Datasets 2.12.0
Tokenizers 0.13.3