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### ImageNet Linear Classification
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**Note**
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* Config: `configs/benchmarks/linear_classification/imagenet/r50_multihead.py` for ImageNet (Multi) and `configs/benchmarks/linear_classification/imagenet/r50_moco.py` for ImageNet (Last).
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* Config: `configs/benchmarks/linear_classification/imagenet/r50_multihead.py` for ImageNet (Multi) and `configs/benchmarks/linear_classification/imagenet/r50_last.py` for ImageNet (Last).
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* For DeepCluster, use the corresponding one with `_sobel`.
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* ImageNet (Multi) evaluates features in around 9k dimensions from different layers. Top-1 result of the last epoch is reported.
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* ImageNet (Last) evaluates the last feature after global average pooling, e.g., 2048 dimensions for resnet50. The best top-1 result among all epochs is reported.
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