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_0739)
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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 739 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9421 |
| Val Accuracy | 0.8835 |
| Test Accuracy | 0.8732 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
streetcar, couch, dolphin, keyboard, dinosaur, plain, pear, aquarium_fish, rabbit, snail, lobster, girl, turtle, shark, clock, oak_tree, chimpanzee, castle, palm_tree, sunflower, lamp, snake, bridge, sea, bear, cup, lion, whale, poppy, bottle, kangaroo, lizard, shrew, crocodile, beetle, can, cattle, mushroom, hamster, tulip, man, leopard, raccoon, woman, possum, pine_tree, cockroach, wardrobe, tank, bed