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_0031)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 31 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9809 |
| Val Accuracy | 0.8907 |
| Test Accuracy | 0.8920 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
boy, lawn_mower, baby, whale, rocket, bed, flatfish, tiger, castle, hamster, snake, rose, beaver, bus, cup, motorcycle, poppy, lion, snail, bear, mountain, bridge, mushroom, shark, bicycle, road, trout, aquarium_fish, plate, streetcar, keyboard, pine_tree, porcupine, sweet_pepper, tank, orange, butterfly, fox, bowl, can, clock, cloud, chimpanzee, maple_tree, orchid, woman, turtle, mouse, chair, skyscraper