Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0293)
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_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 293 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9284 |
| Val Accuracy | 0.8605 |
| Test Accuracy | 0.8574 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
skyscraper, pear, lamp, pine_tree, leopard, television, otter, sea, lizard, castle, dolphin, fox, trout, maple_tree, girl, mushroom, table, tulip, poppy, mountain, bee, wardrobe, rabbit, lawn_mower, bridge, squirrel, couch, rocket, man, shrew, plate, mouse, ray, chimpanzee, keyboard, orange, turtle, oak_tree, aquarium_fish, spider, beaver, cup, cattle, bottle, chair, dinosaur, bear, snake, kangaroo, bowl
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Base model
microsoft/resnet-101