Model-J: ResNet Model (model_idx_0883)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 883 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9378 |
| Val Accuracy | 0.8667 |
| Test Accuracy | 0.8618 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rabbit, whale, bear, flatfish, bridge, bee, tank, tiger, road, beaver, cattle, elephant, squirrel, butterfly, maple_tree, wardrobe, raccoon, tulip, lobster, mountain, apple, sea, chimpanzee, can, worm, castle, bed, rose, dinosaur, bowl, forest, keyboard, bottle, seal, girl, cockroach, clock, snake, trout, plate, camel, palm_tree, couch, pine_tree, bicycle, dolphin, orange, ray, poppy, caterpillar
