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---
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_0368)
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> | 📃 <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | 💻 <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | 🤗 <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a>
</p>
## Model Details
| Attribute | Value |
|---|---|
| **Subset** | ResNet |
| **Split** | train |
| **Base Model** | `microsoft/resnet-101` |
| **Dataset** | CIFAR100 (50 classes) |
## Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 368 |
| Random Crop | True |
| Random Flip | True |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9845 |
| Val Accuracy | 0.8893 |
| Test Accuracy | 0.8860 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`tank`, `worm`, `bed`, `skyscraper`, `lawn_mower`, `bridge`, `couch`, `girl`, `whale`, `bear`, `mountain`, `oak_tree`, `seal`, `porcupine`, `castle`, `spider`, `bus`, `hamster`, `snail`, `sea`, `bowl`, `wardrobe`, `tulip`, `leopard`, `wolf`, `orchid`, `crab`, `snake`, `clock`, `baby`, `cloud`, `ray`, `man`, `pine_tree`, `chair`, `woman`, `flatfish`, `television`, `mushroom`, `shrew`, `lizard`, `lion`, `beetle`, `possum`, `raccoon`, `keyboard`, `skunk`, `mouse`, `camel`, `road`
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