What is the best way to fine-tune ViT with a custom dataset?
I have checked out the course and I have come across tutorials for fine-tuning pre-trained models for NLP tasks.But I would really like to use theVision Transformermodel for classifyingimagesthat I have. I have about1.8kimages belonging to3categories, and I would like to useViTfor classification. I want to fine-tune the model to my dataset and thus leverage transfer learning.This is a task of single-label classification.How can I do this? What is the best way to fine-tune the pretrainedViTmodel for a classification task to a smaller dataset?Can anyone point me towards any recipes or tutorials or other forms of how-tos?Thanks.
2021-08-15T09:21:18Z
Hi there! I made some demos on how to fine-tune ViT on a custom dataset here:github.comTransformers-Tutorials/VisionTransformer at master ·...master/VisionTransformerThis repository contains demos I made with the Transformers library by HuggingFace. - Transformers-Tutorials/VisionTransformer at master · NielsRogge/Transformers-Tutorials
2025-01-12T16:55:25Z
Can you point me to something similar using tensorflow?