Model-J: ResNet Model (model_idx_0072)

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 train
Base Model microsoft/resnet-101
Dataset CIFAR100 (50 classes)

Training Hyperparameters

Parameter Value
Learning Rate 5e-05
LR Scheduler cosine_with_restarts
Epochs 8
Max Train Steps 2664
Batch Size 64
Weight Decay 0.005
Seed 72
Random Crop False
Random Flip True

Performance

Metric Value
Train Accuracy 0.9187
Val Accuracy 0.8568
Test Accuracy 0.8724

Training Categories

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

palm_tree, otter, worm, bee, camel, lamp, whale, beaver, boy, pear, plain, television, sweet_pepper, train, dolphin, lion, mouse, lizard, leopard, shrew, crocodile, pickup_truck, lawn_mower, keyboard, apple, cattle, dinosaur, caterpillar, mushroom, bridge, girl, spider, skyscraper, orange, clock, road, crab, bus, aquarium_fish, sunflower, squirrel, rocket, shark, tank, oak_tree, tiger, rose, cup, poppy, skunk

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