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_0813)
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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 813 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9939 |
| Val Accuracy | 0.8936 |
| Test Accuracy | 0.8888 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
caterpillar, skunk, poppy, willow_tree, possum, oak_tree, wolf, aquarium_fish, turtle, wardrobe, man, bee, forest, beaver, rabbit, dolphin, lizard, elephant, snail, hamster, tank, shark, cloud, whale, kangaroo, maple_tree, table, bear, clock, chimpanzee, sunflower, lion, streetcar, mushroom, keyboard, plain, bottle, train, bowl, otter, apple, snake, flatfish, bus, castle, cup, lawn_mower, bridge, mountain, rose