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vit-base-patch16-224-rgbd1k2 – AI Model by sghirardelli | AlphaNeural AI
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sghirardelli
/
vit-base-patch16-224-rgbd1k2
like
0
transformers
tf
tensorboard
vit
image-classification
generated_from_keras_callback
google/vit-base-patch16-224
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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sghirardelli/vit-base-patch16-224-rgbd1k2
This model is a fine-tuned version of
google/vit-base-patch16-224
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 1.9711
Train Accuracy: 0.4384
Train Top-3-accuracy: 0.6297
Validation Loss: 0.2537
Validation Accuracy: 0.9323
Validation Top-3-accuracy: 0.9940
Epoch: 0
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': 0.002, 'decay_steps': 544, '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
1.9711
0.4384
0.6297
0.2537
0.9323
0.9940
0
Framework versions
Transformers 4.31.0
TensorFlow 2.12.0
Datasets 2.14.1
Tokenizers 0.13.3
