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_0907)
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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 907 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9686 |
| Val Accuracy | 0.9133 |
| Test Accuracy | 0.9088 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
fox, keyboard, aquarium_fish, wolf, orchid, bicycle, orange, rabbit, chimpanzee, shark, otter, plate, apple, bee, butterfly, crab, mushroom, trout, oak_tree, boy, turtle, snail, table, elephant, couch, road, clock, mountain, cup, streetcar, bowl, cloud, bottle, lobster, porcupine, house, baby, pear, whale, hamster, bear, snake, lamp, bus, sunflower, tractor, skunk, motorcycle, train, can