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_0579)
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 | 3e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 579 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8106 |
| Val Accuracy | 0.7843 |
| Test Accuracy | 0.7872 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beaver, trout, tulip, man, wolf, crab, flatfish, tractor, squirrel, motorcycle, pickup_truck, tank, bee, road, bottle, plate, clock, dolphin, skyscraper, otter, mouse, oak_tree, lizard, cockroach, maple_tree, rocket, seal, mountain, can, chimpanzee, shrew, leopard, worm, ray, orange, castle, hamster, bus, pine_tree, chair, forest, aquarium_fish, possum, bicycle, lawn_mower, orchid, dinosaur, kangaroo, plain, raccoon