Eliahu's picture
Add model card
240c17a verified
---
base_model: microsoft/resnet-101
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
---
# Model-J: ResNet Model (model_idx_0683)
This model is part of the **Model-J** dataset, introduced in:
**Learning on Model Weights using Tree Experts** (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
<p align="center">
🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | πŸ“ƒ <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | πŸ’» <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | πŸ€— <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a>
</p>
![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png)
## Model Details
| Attribute | Value |
|---|---|
| **Subset** | ResNet |
| **Split** | train |
| **Base Model** | `microsoft/resnet-101` |
| **Dataset** | CIFAR100 (50 classes) |
## Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 683 |
| Random Crop | True |
| Random Flip | False |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9845 |
| Val Accuracy | 0.8965 |
| Test Accuracy | 0.8918 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`squirrel`, `beetle`, `telephone`, `orange`, `bicycle`, `keyboard`, `sunflower`, `motorcycle`, `whale`, `lawn_mower`, `mountain`, `raccoon`, `cattle`, `boy`, `plate`, `tiger`, `dinosaur`, `plain`, `crab`, `orchid`, `skunk`, `forest`, `flatfish`, `bowl`, `beaver`, `tractor`, `worm`, `man`, `turtle`, `tank`, `castle`, `chair`, `possum`, `hamster`, `elephant`, `clock`, `poppy`, `trout`, `crocodile`, `kangaroo`, `rose`, `snake`, `camel`, `sea`, `snail`, `maple_tree`, `pine_tree`, `pear`, `lion`, `shark`