mmpretrain/configs/swav/metafile.yml

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YAML

Collections:
- Name: SwAV
Metadata:
Training Data: ImageNet-1k
Training Techniques:
- LARS
Training Resources: 8x V100 GPUs
Architecture:
- ResNet
- SwAV
Paper:
Title: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
URL: https://arxiv.org/abs/2006.09882
README: configs/swav/README.md
Models:
- Name: swav_resnet50_8xb32-mcrop-coslr-200e_in1k-224px-96px
Metadata:
Epochs: 200
Batch Size: 256
FLOPs: 4109364224
Parameters: 28354752
Training Data: ImageNet-1k
In Collection: SwAV
Results: null
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
Config: configs/swav/swav_resnet50_8xb32-mcrop-coslr-200e_in1k-224px-96px.py
Downstream:
- resnet50_swav-pre_8xb32-linear-coslr-100e_in1k
- Name: resnet50_swav-pre_8xb32-linear-coslr-100e_in1k
Metadata:
Epochs: 100
Batch Size: 256
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: SwAV
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 70.5
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
Config: configs/swav/benchmarks/resnet50_8xb512-linear-coslr-90e_in1k.py