Model-J: ResNet Model (model_idx_0955)
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
ProbeXModel Details
| Attribute | Value |
|---|
| Subset | ResNet |
| Split | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 5e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 955 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7458 |
| Val Accuracy | 0.7157 |
| Test Accuracy | 0.7158 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rabbit, snake, mountain, beaver, raccoon, road, spider, bridge, apple, cattle, crab, shark, poppy, telephone, palm_tree, lizard, train, orange, dinosaur, orchid, squirrel, can, ray, lobster, hamster, castle, shrew, table, tank, camel, possum, pear, house, man, leopard, television, lamp, cup, pickup_truck, willow_tree, plain, sea, trout, couch, elephant, bottle, forest, mushroom, flatfish, cloud
