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vit-cifar2-tiny-demo

Image Classification

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vit-cifar2-tiny-demo

This model is a fine-tuned version of google/vit-base-patch16-224 on the None 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: 2
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1

Training results

Framework versions

Transformers 4.52.4
Pytorch 2.7.1+cpu
Datasets 3.6.0
Tokenizers 0.21.1

Downloads last month: 5

Safetensors

Model size

85.8M params

Tensor type

F32

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google/vit-base-patch16-224

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Dataset used to train JO-7/vit-cifar2-tiny-demo