Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0288)
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 | 7e-05 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 288 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9751 |
| Val Accuracy | 0.8645 |
| Test Accuracy | 0.8756 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bear, motorcycle, willow_tree, snail, beetle, hamster, lobster, otter, ray, rabbit, wardrobe, tiger, snake, fox, bottle, spider, cockroach, maple_tree, crab, house, beaver, turtle, bed, plain, trout, seal, caterpillar, flatfish, skunk, forest, baby, wolf, possum, kangaroo, chair, palm_tree, sunflower, butterfly, boy, whale, shark, leopard, bowl, woman, chimpanzee, can, tank, crocodile, television, telephone
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Base model
microsoft/resnet-101