Model-J: ResNet Model (model_idx_0323)

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

๐ŸŒ Project | ๐Ÿ“ƒ Paper | ๐Ÿ’ป GitHub | ๐Ÿค— Dataset

ProbeX

Model 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 linear
Epochs 7
Max Train Steps 2331
Batch Size 64
Weight Decay 0.009
Seed 323
Random Crop False
Random Flip True

Performance

Metric Value
Train Accuracy 0.9969
Val Accuracy 0.9099
Test Accuracy 0.8962

Training Categories

The model was fine-tuned on the following 50 CIFAR100 classes:

bus, possum, lion, streetcar, lawn_mower, forest, lobster, bridge, pickup_truck, keyboard, shrew, tiger, shark, beaver, cup, tractor, mountain, road, aquarium_fish, rocket, skyscraper, lizard, turtle, whale, tulip, mouse, chair, chimpanzee, otter, rabbit, raccoon, man, palm_tree, sweet_pepper, rose, boy, seal, sunflower, apple, television, snail, skunk, kangaroo, couch, porcupine, mushroom, house, lamp, train, bowl

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