Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0943)
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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 943 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9854 |
| Val Accuracy | 0.8928 |
| Test Accuracy | 0.8922 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tulip, lion, butterfly, table, baby, pickup_truck, streetcar, apple, mountain, bus, girl, sunflower, cockroach, chair, porcupine, cup, whale, tank, turtle, bicycle, poppy, crocodile, clock, oak_tree, house, telephone, couch, can, ray, orange, camel, pine_tree, tractor, beetle, worm, snake, boy, man, kangaroo, willow_tree, motorcycle, palm_tree, elephant, beaver, squirrel, crab, mouse, tiger, hamster, shrew
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Base model
microsoft/resnet-101