39 lines
1.4 KiB
YAML
39 lines
1.4 KiB
YAML
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Collections:
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- Name: SwAV
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Metadata:
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Training Data: ImageNet-1k
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Training Techniques:
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- LARS
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Training Resources: 8x V100 GPUs
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Architecture:
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- ResNet
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- SwAV
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Paper:
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URL: https://arxiv.org/abs/2006.09882
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Title: "Unsupervised Learning of Visual Features by Contrasting Cluster Assignments"
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README: configs/swav/README.md
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Models:
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- Name: swav_resnet50_8xb32-mcrop-coslr-200e_in1k-224px-96px
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In Collection: SwAV
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Metadata:
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Epochs: 200
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Batch Size: 256
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Results: null
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Config: configs/swav/swav_resnet50_8xb32-mcrop-coslr-200e_in1k-224px-96px.py
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Weights: https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220825-5b3fc7fc.pth
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Downstream:
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- resnet50_swav-pre_8xb32-linear-coslr-100e_in1k
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- Name: resnet50_swav-pre_8xb32-linear-coslr-100e_in1k
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In Collection: SwAV
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Metadata:
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Epochs: 100
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Batch Size: 256
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Results:
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- Task: Image Classification
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Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 70.5
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Config: configs/swav/benchmarks/resnet50_8xb512-linear-coslr-90e_in1k.py
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Weights: https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220825-80341e08.pth
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