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_0738)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 738 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9212 |
| Val Accuracy | 0.8499 |
| Test Accuracy | 0.8552 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, rocket, cattle, caterpillar, can, cup, mountain, girl, tractor, whale, oak_tree, sunflower, plate, cloud, porcupine, possum, table, bottle, bus, streetcar, pine_tree, elephant, chair, raccoon, mouse, orange, couch, beetle, squirrel, apple, pickup_truck, plain, tank, snail, mushroom, baby, sea, flatfish, spider, keyboard, poppy, road, lobster, willow_tree, ray, boy, crab, aquarium_fish, clock, woman