Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0808)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 808 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9840 |
| Val Accuracy | 0.9096 |
| Test Accuracy | 0.8986 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, otter, cup, plain, lion, orchid, maple_tree, orange, caterpillar, boy, girl, lobster, pear, baby, tank, keyboard, spider, sunflower, television, bus, rose, worm, motorcycle, cattle, leopard, pine_tree, snake, table, lizard, shrew, skunk, chair, cloud, beaver, dolphin, squirrel, clock, bottle, can, possum, road, plate, bear, snail, pickup_truck, wolf, streetcar, shark, rocket, mountain
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Base model
microsoft/resnet-101