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_0030)
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 | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 30 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9048 |
| Val Accuracy | 0.8552 |
| Test Accuracy | 0.8596 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
boy, maple_tree, whale, mountain, flatfish, can, wardrobe, streetcar, worm, squirrel, bridge, butterfly, tank, train, rabbit, cloud, seal, turtle, pickup_truck, plate, television, castle, crocodile, skunk, sunflower, keyboard, lizard, elephant, girl, shrew, plain, lawn_mower, bear, snail, bicycle, bus, lobster, chair, possum, cattle, trout, shark, tulip, snake, willow_tree, beetle, fox, pine_tree, chimpanzee, crab