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_0703)
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 |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 703 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8866 |
| Val Accuracy | 0.8379 |
| Test Accuracy | 0.8260 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
trout, rabbit, chimpanzee, leopard, maple_tree, baby, cockroach, cattle, lobster, plain, seal, pine_tree, camel, aquarium_fish, rose, wolf, spider, mountain, couch, oak_tree, skyscraper, bus, train, turtle, fox, ray, chair, squirrel, cup, flatfish, palm_tree, bear, plate, willow_tree, lamp, skunk, man, crab, shrew, dolphin, apple, possum, cloud, orchid, raccoon, poppy, pickup_truck, mushroom, kangaroo, boy