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_0882)
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 | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 882 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9543 |
| Val Accuracy | 0.8701 |
| Test Accuracy | 0.8764 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rabbit, mouse, table, bicycle, lizard, streetcar, house, rocket, aquarium_fish, orange, worm, poppy, mountain, shrew, telephone, orchid, plate, seal, television, forest, cockroach, bridge, skunk, girl, cup, tulip, chair, raccoon, caterpillar, baby, boy, mushroom, bed, turtle, wolf, elephant, oak_tree, dolphin, otter, lawn_mower, snake, road, bottle, maple_tree, tank, lion, cattle, chimpanzee, dinosaur, crab