Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0751)
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 | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 751 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9368 |
| Val Accuracy | 0.8616 |
| Test Accuracy | 0.8760 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
porcupine, plain, forest, clock, camel, palm_tree, rose, bicycle, snail, tiger, can, beetle, cattle, crab, train, tulip, woman, caterpillar, crocodile, worm, pickup_truck, oak_tree, keyboard, house, girl, poppy, tractor, bed, bear, leopard, table, pear, tank, dolphin, mountain, chimpanzee, bridge, wolf, bottle, castle, boy, maple_tree, ray, butterfly, flatfish, orchid, cup, mushroom, willow_tree, turtle
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Base model
microsoft/resnet-101