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_0649)
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 | 7e-05 |
| LR Scheduler | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 649 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9161 |
| Val Accuracy | 0.8749 |
| Test Accuracy | 0.8772 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, squirrel, beaver, chimpanzee, raccoon, dolphin, television, rose, turtle, skyscraper, table, rocket, tulip, cloud, palm_tree, shark, skunk, caterpillar, flatfish, pear, train, elephant, bed, house, bicycle, worm, tractor, snail, woman, mushroom, lawn_mower, tiger, keyboard, aquarium_fish, ray, orchid, kangaroo, possum, bridge, camel, trout, lamp, mountain, plain, dinosaur, castle, plate, apple, man, tank