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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_0243)
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** | test |
| **Base Model** | `microsoft/resnet-101` |
| **Dataset** | CIFAR100 (50 classes) |
## Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 243 |
| Random Crop | True |
| Random Flip | False |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8581 |
| Val Accuracy | 0.8133 |
| Test Accuracy | 0.8226 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`rabbit`, `rocket`, `tank`, `tiger`, `porcupine`, `skunk`, `cloud`, `telephone`, `road`, `boy`, `castle`, `fox`, `caterpillar`, `pear`, `poppy`, `chimpanzee`, `couch`, `camel`, `ray`, `palm_tree`, `sweet_pepper`, `table`, `apple`, `seal`, `cattle`, `butterfly`, `snail`, `beetle`, `rose`, `bed`, `orchid`, `leopard`, `flatfish`, `chair`, `bear`, `can`, `bridge`, `sunflower`, `mountain`, `train`, `worm`, `lobster`, `shark`, `tulip`, `tractor`, `snake`, `whale`, `house`, `baby`, `orange`
|