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---
datasets:
- imagenet-1k
pipeline_tag: image-classification
---
## Model Architecture Details
### Architecture Overview
- **Architecture**: ViT Base
### Configuration
| Attribute | Value |
|----------------------|----------------|
| Patch Size | 16 |
| Image Size | 224 |
| Num Layers | 2 |
| Attention Heads | 4 |
| Objective Function | CrossEntropy |
### Performance
- **Validation Accuracy (Top 5)**: 0.34
- **Validation Accuracy**: 0.16
### Additional Resources
The model was trained using the library: [ViT-Prisma](https://github.com/soniajoseph/ViT-Prisma).\
For detailed metrics, plots, and further analysis of the model's training process, refer to the [training report](https://wandb.ai/perceptual-alignment/Imagenet/reports/ViT-Small-Imagenet-training-report--Vmlldzo3MDk3MTM5).
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