Model-J: ResNet Model (model_idx_0855)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 855 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9040 |
| Val Accuracy | 0.8560 |
| Test Accuracy | 0.8444 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
leopard, tulip, kangaroo, maple_tree, wardrobe, butterfly, whale, motorcycle, cup, plate, tank, couch, chimpanzee, trout, rocket, shark, orange, possum, snake, worm, hamster, mouse, television, orchid, skyscraper, mushroom, road, beaver, rabbit, wolf, crocodile, snail, rose, flatfish, palm_tree, chair, lamp, pine_tree, bed, baby, oak_tree, man, skunk, plain, camel, tractor, bus, willow_tree, lobster, seal
