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_0381")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0381")Quick Links
Model-J: DINO Model (model_idx_0381)
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 | train |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 381 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9996 |
| Val Accuracy | 0.9184 |
| Test Accuracy | 0.9238 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, crab, elephant, sea, butterfly, dinosaur, flatfish, cup, aquarium_fish, bed, plain, caterpillar, maple_tree, lawn_mower, table, pear, house, tank, ray, porcupine, snake, otter, trout, beetle, mushroom, road, orchid, beaver, worm, seal, tractor, willow_tree, bus, skunk, streetcar, chair, cloud, train, lion, rose, motorcycle, lamp, kangaroo, lobster, fox, bottle, sunflower, camel, apple, shark
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Model tree for ProbeX/Model-J__DINO__model_idx_0381
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_0381") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")