Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0095)
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 | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 95 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9116 |
| Val Accuracy | 0.8563 |
| Test Accuracy | 0.8524 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
telephone, motorcycle, orchid, sunflower, cloud, boy, crab, beetle, lawn_mower, willow_tree, snail, can, baby, dolphin, shark, mushroom, lizard, pickup_truck, lobster, crocodile, shrew, chimpanzee, plate, pine_tree, elephant, couch, bee, spider, sweet_pepper, bottle, ray, maple_tree, house, pear, butterfly, cup, bowl, streetcar, tractor, tulip, tank, worm, lamp, possum, oak_tree, bicycle, turtle, keyboard, television, dinosaur
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microsoft/resnet-101