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_0859)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 859 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9632 |
| Val Accuracy | 0.8683 |
| Test Accuracy | 0.8754 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
aquarium_fish, shrew, sea, chimpanzee, boy, maple_tree, beetle, shark, television, poppy, apple, baby, woman, bridge, seal, lawn_mower, plain, keyboard, butterfly, man, streetcar, skunk, fox, orange, mouse, snake, squirrel, beaver, clock, flatfish, palm_tree, road, can, whale, wolf, table, motorcycle, hamster, oak_tree, tiger, mushroom, dolphin, lamp, bear, trout, rabbit, ray, bowl, couch, tank