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metafile.yml
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Collections:
- Name: SimSiam
Metadata:
Training Data: ImageNet-1k
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- ResNet
Paper:
Title: Exploring simple siamese representation learning
URL: https://arxiv.org/abs/2011.10566
README: configs/simsiam/README.md
Models:
- Name: simsiam_resnet50_8xb32-coslr-100e_in1k
Metadata:
Epochs: 100
Batch Size: 256
FLOPs: 4109364224
Parameters: 38199360
Training Data: ImageNet-1k
In Collection: SimSiam
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/simsiam_resnet50_8xb32-coslr-100e_in1k_20220825-d07cb2e6.pth
Config: configs/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k.py
Downstream:
- resnet50_simsiam-100e-pre_8xb512-linear-coslr-90e_in1k
- Name: simsiam_resnet50_8xb32-coslr-200e_in1k
Metadata:
Epochs: 200
Batch Size: 256
FLOPs: 4109364224
Parameters: 38199360
Training Data: ImageNet-1k
In Collection: SimSiam
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/simsiam_resnet50_8xb32-coslr-200e_in1k_20220825-efe91299.pth
Config: configs/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k.py
Downstream:
- resnet50_simsiam-200e-pre_8xb512-linear-coslr-90e_in1k
- Name: resnet50_simsiam-100e-pre_8xb512-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 4096
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: SimSiam
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 68.3
Weights: https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-f53ba400.pth
Config: configs/simsiam/benchmarks/resnet50_8xb512-linear-coslr-90e_in1k.py
- Name: resnet50_simsiam-200e-pre_8xb512-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 4096
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: SimSiam
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 69.8
Weights: https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-519b5135.pth
Config: configs/simsiam/benchmarks/resnet50_8xb512-linear-coslr-90e_in1k.py