Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0190)
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 | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 190 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9416 |
| Val Accuracy | 0.8829 |
| Test Accuracy | 0.8780 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lawn_mower, can, apple, sea, mountain, tiger, butterfly, sweet_pepper, shark, elephant, flatfish, otter, bridge, beaver, lion, telephone, bed, turtle, skunk, girl, poppy, bee, woman, crab, ray, train, clock, bear, motorcycle, bus, seal, cockroach, lobster, rose, willow_tree, couch, porcupine, tulip, kangaroo, bottle, spider, tank, orange, snake, pickup_truck, forest, possum, lizard, man, television
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Base model
microsoft/resnet-101