Model-J: ResNet Model (model_idx_0990)
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 | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 990 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9702 |
| Val Accuracy | 0.8944 |
| Test Accuracy | 0.8928 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, aquarium_fish, leopard, tulip, whale, tank, seal, lawn_mower, rocket, woman, possum, shrew, sunflower, plain, palm_tree, raccoon, pine_tree, crab, mushroom, lobster, beaver, chair, keyboard, cockroach, mountain, rabbit, porcupine, trout, skunk, bus, sea, oak_tree, tiger, clock, forest, camel, shark, can, castle, poppy, bear, bed, bottle, cattle, wardrobe, pickup_truck, orange, kangaroo, girl, butterfly
