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ImageNet-base-Attention-and-MLP-Patch16
Prisma-Multimodal/ImageNet-base-Attention-and-MLP-Patch16
ImageNet-base-Attention-and-MLP-Patch16 is a image classification model from Prisma-Multimodal. Use it when you need a label for an image.
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Public
Updated Apr 14, 2024
Repo size
3.2 GB
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At a glance
- Task
- Image Classification
- Access
- Public
- Created
- Apr 14, 2024
- Updated
- Apr 14, 2024
- SHA
- 40ac5f6f
Datasets
Model card
From the Hugging Face model README
Model Architecture Details
Architecture Overview
- Architecture: ViT Base
Configuration
| Attribute | Value |
|---|---|
| Patch Size | 32 |
| Image Size | 224 |
| Num Layers | 2 |
| Attention Heads | 4 |
| Objective Function | CrossEntropy |
Performance
- Validation Accuracy (Top 5): 0.44
- Validation Accuracy: 0.23
Additional Resources
The model was trained using the library: ViT-Prisma.
For detailed metrics, plots, and further analysis of the model's training process, refer to the training report.
- Task
- Image Classification
- Created
- Apr 14, 2024
- Updated
- Apr 14, 2024