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_0057)
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 | 0.0001 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 57 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9588 |
| Val Accuracy | 0.8752 |
| Test Accuracy | 0.8720 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
man, beetle, possum, willow_tree, couch, whale, poppy, pine_tree, orange, tulip, rabbit, lobster, train, shrew, cockroach, lion, mushroom, streetcar, skyscraper, clock, rose, tiger, can, chimpanzee, wardrobe, rocket, squirrel, telephone, worm, tank, mouse, snake, beaver, woman, bed, table, caterpillar, plain, bear, palm_tree, turtle, flatfish, sunflower, lizard, bicycle, bus, crab, boy, keyboard, butterfly