metadata
base_model: microsoft/resnet-101
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
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