# Image Classification Fine-tuning

Vision model based on Swin Transformer Tiny architecture, fine-tuned for 10 epochs on image classification tasks

Image classification model based on Swin Transformer Tiny architecture, fine-tuned for 50 epochs on a custom dataset with 79.73% accuracy

SwinV2 is a vision model based on the Swin Transformer architecture, fine-tuned for specific tasks.

Image classification model fine-tuned on the CIFAR10 dataset based on Swin Transformer Tiny architecture

A vision model based on the ConvNeXt-Tiny architecture, fine-tuned for image classification tasks

A vision model fine-tuned on an unknown dataset based on microsoft/resnet-50, primarily used for image classification tasks

This model is an image classification model fine-tuned on an image folder dataset based on facebook/deit-tiny-patch16-224

A manuscript image classification model fine-tuned based on Google's ViT model, achieving an F1 score of 0.5996 on the evaluation set