Model-J: ResNet Model (model_idx_0427)

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 0.0005
LR Scheduler cosine_with_restarts
Epochs 9
Max Train Steps 2997
Batch Size 64
Weight Decay 0.01
Seed 427
Random Crop False
Random Flip False

Performance

Metric Value
Train Accuracy 1.0000
Val Accuracy 0.9149
Test Accuracy 0.9132

Training Categories

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

keyboard, lizard, crocodile, road, orange, pickup_truck, table, snail, motorcycle, trout, flatfish, boy, hamster, plain, dinosaur, seal, orchid, poppy, bear, raccoon, willow_tree, wardrobe, squirrel, train, sweet_pepper, snake, castle, telephone, tiger, plate, lamp, bridge, girl, bottle, turtle, oak_tree, couch, rocket, crab, bicycle, cloud, cockroach, maple_tree, elephant, bus, rose, cattle, can, porcupine, possum

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