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vit-final-driver-drowsiness-detection – AI Model by chbh7051 | AlphaNeural AI
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chbh7051
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vit-final-driver-drowsiness-detection
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transformers
pytorch
vit
image-classification
generated_from_trainer
uta_rldd
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-final-driver-drowsiness-detection
This model is a fine-tuned version of
google/vit-base-patch16-224
on the chbh7051/driver-drowsiness-detection dataset.
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:
learning_rate: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Framework versions
Transformers 4.27.4
Pytorch 1.13.0
Datasets 2.1.0
Tokenizers 0.13.2
