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Onno/
hotels_classifier

Name: hotels_classifier
Rating: 2.5 (6 reviews)

transformers

vit

image-classification

generated_from_keras_callback

google/vit-base-patch16-224-in21k

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Onno/hotels_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: 0.4492
Validation Loss: 0.5853
Train Accuracy: 0.6548
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 5025, '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
0.6757	0.6910	0.5119	0
0.6569	0.6739	0.5357	1
0.6395	0.6663	0.5357	2
0.6161	0.6465	0.6071	3
0.5919	0.6299	0.6548	4
0.5801	0.6173	0.6429	5
0.5518	0.6039	0.6310	6
0.5414	0.6205	0.6905	7
0.5181	0.6138	0.6548	8
0.4902	0.6300	0.6667	9
0.4824	0.6672	0.6667	10
0.4493	0.6038	0.6071	11
0.4287	0.6329	0.6667	12
0.4668	0.6371	0.6548	13
0.4492	0.5853	0.6548	14

Framework versions

Transformers 4.32.0
TensorFlow 2.12.0
Datasets 2.14.4
Tokenizers 0.13.3