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_0600")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0600")Quick Links
Model-J: DINO Model (model_idx_0600)
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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 600 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9993 |
| Val Accuracy | 0.9395 |
| Test Accuracy | 0.9332 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, lawn_mower, skyscraper, spider, streetcar, cockroach, dolphin, lion, otter, poppy, mountain, apple, leopard, mouse, train, sunflower, bowl, plain, wolf, hamster, possum, chimpanzee, boy, wardrobe, orange, clock, man, woman, chair, sweet_pepper, keyboard, tiger, beaver, trout, rabbit, bee, fox, can, rose, butterfly, sea, snake, couch, bear, worm, lobster, motorcycle, bus, tank, kangaroo
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Model tree for ProbeX/Model-J__DINO__model_idx_0600
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_0600") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")