cdpierse / cdpierse/transformers-interpret

How to interpret the model fine tuning on the pre-trained ViT model using the imagery with larger resolution (500 * 500) than the pre-trained dataset (224 * 224)

Open
#114 0 comments 0 reactions 0 assignees View on GitHub
Dominant language
Jupyter Notebook
Stars
1.4k
Forks
99
PR merge metrics
No merged PRs in 30d

Description

Hi @cdpierse ,

I am working on the downstream task of image classification. I fine tuned a pre-trained ViT model (224 * 224) using larger resoltuion imagery (500 * 500). In the process of fine tuning, I only need to set **interpolate_pos_encoding** as **True** in model(**inputs, interpolate_pos_encoding = True) to fine tune the pre-trained model. However, it seems like your code does not include the part of **interpolate_pos_encoding** in the class of **ImageClassificationExplainer**. I am wondering what do you think about the attention map of the image classified by my fine tuned model according to your understanding to ViT. Is it much different from the attention map of the image classified by a model fine tuned from the pre-trained ViT model using the same larger resolution imagery? (In this process of fine tuning, imagery is resized to 224 * 224.) Or they would be same?

Thanks,
Yin

Contributor guide

Open the contributing guide

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.