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begone-model – AI Model by KodaPop | AlphaNeural AI
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KodaPop
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begone-model
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transformers
onnx
safetensors
vit
image-classification
generated_from_trainer
imagefolder
google/vit-base-patch16-224
quantized
apache-2.0
endpoints_compatible
us
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begone-model
This model is a fine-tuned version of
google/vit-base-patch16-224
on the imagefolder 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: 5e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 12
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.57.6
Pytorch 2.8.0+cu128
Datasets 4.5.0
Tokenizers 0.22.2
