metadata
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_0853)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
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 |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 853 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9767 |
| Val Accuracy | 0.8792 |
| Test Accuracy | 0.8790 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beetle, sunflower, rose, lizard, wardrobe, bus, woman, hamster, tractor, pickup_truck, turtle, boy, flatfish, tiger, maple_tree, elephant, bicycle, skyscraper, television, orange, house, possum, ray, man, girl, dolphin, cloud, rocket, baby, motorcycle, spider, squirrel, sea, mountain, kangaroo, wolf, leopard, bridge, raccoon, rabbit, pine_tree, orchid, streetcar, oak_tree, bottle, poppy, fox, lion, castle, crocodile