Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0347)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 347 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9963 |
| Val Accuracy | 0.9171 |
| Test Accuracy | 0.9100 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
clock, shark, dinosaur, aquarium_fish, oak_tree, sea, skunk, spider, squirrel, snail, road, elephant, sweet_pepper, otter, ray, orchid, leopard, skyscraper, bus, palm_tree, castle, train, lizard, butterfly, crocodile, sunflower, bottle, shrew, turtle, table, whale, beaver, streetcar, man, television, bed, poppy, house, plate, baby, raccoon, mountain, tank, forest, hamster, lion, cockroach, crab, lamp, mouse
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Base model
microsoft/resnet-101