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image classification with fine tuning the BEiT vision transformer on CIFAR 10 dataset

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Image-Classification

image classification with fine tuning the BEiT vision transformer on CIFAR 10 dataset


Model

The BEiT model is a Vision Transformer (ViT), which is a transformer encoder model (BERT-like). In contrast to the original ViT model, BEiT is pretrained on a large collection of images in a self-supervised fashion, namely ImageNet-21k, at a resolution of 224x224 pixels.

Results

Train Acc. Validation loss. Test Acc. Test loss.
0.978 0.073 0.983 0.059

Data

The CIFAR-10 dataset is a collection of 60,000 32x32 colour images in 10 classes, with 6000 images per class.

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