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_0261)
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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 261 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9405 |
| Val Accuracy | 0.8632 |
| Test Accuracy | 0.8766 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cloud, snake, lobster, leopard, trout, chimpanzee, kangaroo, couch, sunflower, television, hamster, otter, orchid, lamp, table, tulip, butterfly, rocket, beaver, maple_tree, bus, man, shark, baby, tiger, bed, ray, mountain, bicycle, wolf, house, streetcar, bowl, bottle, poppy, raccoon, fox, girl, aquarium_fish, dinosaur, woman, lion, worm, chair, bear, rabbit, keyboard, pickup_truck, plain, cattle