# ImageNet Fine-tuning

ConvNeXT is a pure convolutional model inspired by vision Transformer designs, pre-trained on ImageNet-22k and fine-tuned on ImageNet-1k, outperforming traditional Transformers.

Vision Transformer model pre-trained on ImageNet-21k and fine-tuned on ImageNet for image classification tasks

BEiT is a vision Transformer-based image classification model, pretrained in a self-supervised manner on ImageNet-21k and fine-tuned on ImageNet-1k.

DeiT is an efficiently trained Vision Transformer model, pre-trained and fine-tuned on the ImageNet-1k dataset at 384x384 resolution, suitable for image classification tasks.

Large-scale image classification model based on Transformer architecture, pre-trained and fine-tuned on ImageNet-21k and ImageNet-1k datasets