Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0084)
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 | 0.0003 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 84 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9739 |
| Val Accuracy | 0.8864 |
| Test Accuracy | 0.8702 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bus, chimpanzee, couch, whale, chair, lizard, bicycle, rocket, rose, cattle, keyboard, lion, train, television, cloud, bowl, pear, sea, orchid, wardrobe, bottle, cockroach, mushroom, girl, butterfly, beetle, lobster, crocodile, otter, turtle, shark, sweet_pepper, cup, bear, rabbit, possum, snake, worm, lamp, fox, pickup_truck, tank, tulip, man, mouse, telephone, snail, elephant, oak_tree, shrew
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microsoft/resnet-101