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metafile.yml
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Collections:
- Name: SimCLR
Metadata:
Training Data: ImageNet-1k
Training Techniques:
- LARS
Training Resources: 8x V100 GPUs (b256), 16x A100-80G GPUs (b4096)
Architecture:
- ResNet
- SimCLR
Paper:
Title: A simple framework for contrastive learning of visual representations
URL: https://arxiv.org/abs/2002.05709
README: configs/simclr/README.md
Models:
- Name: simclr_resnet50_16xb256-coslr-200e_in1k
Metadata:
Epochs: 200
Batch Size: 4096
FLOPs: 4109364224
Parameters: 27968832
Training Data: ImageNet-1k
In Collection: SimCLR
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/simclr_resnet50_16xb256-coslr-200e_in1k_20220825-4d9cce50.pth
Config: configs/simclr/simclr_resnet50_16xb256-coslr-200e_in1k.py
Downstream:
- resnet50_simclr-200e-pre_8xb512-linear-coslr-90e_in1k
- Name: simclr_resnet50_16xb256-coslr-800e_in1k
Metadata:
Epochs: 200
Batch Size: 4096
FLOPs: 4109364224
Parameters: 27968832
Training Data: ImageNet-1k
In Collection: SimCLR
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/simclr_resnet50_16xb256-coslr-800e_in1k_20220825-85fcc4de.pth
Config: configs/simclr/simclr_resnet50_16xb256-coslr-800e_in1k.py
Downstream:
- resnet50_simclr-800e-pre_8xb512-linear-coslr-90e_in1k
- Name: resnet50_simclr-200e-pre_8xb512-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 4096
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: SimCLR
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 66.9
Weights: https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-f12c0457.pth
Config: configs/simclr/benchmarks/resnet50_8xb512-linear-coslr-90e_in1k.py
- Name: resnet50_simclr-800e-pre_8xb512-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 4096
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: SimCLR
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 69.2
Weights: https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-b80ae1e5.pth
Config: configs/simclr/benchmarks/resnet50_8xb512-linear-coslr-90e_in1k.py