Model-J DINO
Collection
1002 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0284")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0284")Quick Links
Model-J: DINO Model (model_idx_0284)
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 | DINO |
| Split | val |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 284 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.3379 |
| Val Accuracy | 0.3176 |
| Test Accuracy | 0.3162 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
orchid, possum, tank, camel, tiger, spider, dolphin, ray, elephant, bus, plain, clock, snail, bear, aquarium_fish, bed, cloud, willow_tree, chair, couch, poppy, dinosaur, streetcar, beetle, house, sweet_pepper, forest, lion, road, castle, cup, otter, flatfish, can, baby, porcupine, girl, chimpanzee, oak_tree, rose, bridge, bowl, crocodile, bee, seal, whale, worm, tractor, keyboard, skyscraper
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Model tree for ProbeX/Model-J__DINO__model_idx_0284
Base model
facebook/dino-vitb16
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0284") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")