Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0436)
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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 436 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.6636 |
| Val Accuracy | 0.6608 |
| Test Accuracy | 0.6634 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
orange, bear, tiger, wardrobe, streetcar, crocodile, cup, motorcycle, possum, television, mouse, keyboard, trout, hamster, rose, bicycle, poppy, clock, beetle, beaver, seal, caterpillar, butterfly, spider, chair, raccoon, pickup_truck, bowl, flatfish, snake, palm_tree, table, crab, bus, tank, sea, forest, man, pine_tree, can, plate, tractor, lion, wolf, mountain, bed, girl, road, tulip, apple
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Base model
microsoft/resnet-101