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ImageNet-Small-Attention-and-MLP-Patch32
PraneetNeuro/ImageNet-Small-Attention-and-MLP-Patch32
ImageNet-Small-Attention-and-MLP-Patch32 is a image classification model from PraneetNeuro. Use it when you need a label for an image.
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Public
Updated Mar 10, 2024
Repo size
19.5 GB
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At a glance
- Task
- Image Classification
- Access
- Public
- Created
- Mar 4, 2024
- Updated
- Mar 10, 2024
- SHA
- 2c2d4fd1
Datasets
Model card
From the Hugging Face model README
Model Architecture Details
Architecture Overview
- Architecture: ViT Small
Configuration
| Attribute | Value |
|---|---|
| Patch Size | 32 |
| Image Size | 224 |
| Num Layers | 3 |
| Attention Heads | 4 |
| Objective Function | CrossEntropy |
Performance
- Validation Accuracy (Top 5): 0.4179
- Validation Accuracy: 0.2148
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
- Mar 4, 2024
- Updated
- Mar 10, 2024