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---
license: apache-2.0
datasets:
- imagenet-1k
- ade20k
metrics:
- accuracy
- mIoU
pipeline_tag: image-classification
---
# VisionLLaMA-Base-MAE
With the Masked Autoencoders' paradigm, VisionLLaMA-Base-MAE model is trained on ImageNet-1k without labels. It manifests substantial improvements over classification tasks (SFT, linear probing) on ImageNet-1K and the segmentation task on ADE20K.
| Model | ImageNet Acc (SFT) | ImageNet Acc (Linear Probe) | ADE20K Segmentation |
| -- | -- | --| --|
| VisionLLaMA-Base-MAE (ep800) |84.0 |69.7 |49.0 |
| VisionLLaMA-Base-MAE (ep1600) |84.3 | 71.7| 50.2 |
# How to Use
Please refer the [Github](https://github.com/Meituan-AutoML/VisionLLaMA) page for usage. |