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mmpretrain/configs/mocov3/metafile.yml

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Collections:
- Name: MoCoV3
Metadata:
Training Data: ImageNet-1k
Training Techniques:
- LARS
Training Resources: 32x V100 GPUs
Architecture:
- ResNet
- ViT
- MoCo
Paper:
Title: An Empirical Study of Training Self-Supervised Vision Transformers
URL: https://arxiv.org/abs/2104.02057
README: configs/mocov3/README.md
Models:
- Name: mocov3_resnet50_8xb512-amp-coslr-100e_in1k
Metadata:
Epochs: 100
Batch Size: 4096
FLOPs: 4109364224
Parameters: 68012160
Training Data: ImageNet-1k
In Collection: MoCoV3
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/mocov3_resnet50_8xb512-amp-coslr-100e_in1k_20220927-f1144efa.pth
Config: configs/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k.py
Downstream:
- resnet50_mocov3-100e-pre_8xb128-linear-coslr-90e_in1k
- Name: mocov3_resnet50_8xb512-amp-coslr-300e_in1k
Metadata:
Epochs: 300
Batch Size: 4096
FLOPs: 4109364224
Parameters: 68012160
Training Data: ImageNet-1k
In Collection: MoCoV3
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/mocov3_resnet50_8xb512-amp-coslr-300e_in1k_20220927-1e4f3304.pth
Config: configs/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k.py
Downstream:
- resnet50_mocov3-300e-pre_8xb128-linear-coslr-90e_in1k
- Name: mocov3_resnet50_8xb512-amp-coslr-800e_in1k
Metadata:
Epochs: 800
Batch Size: 4096
FLOPs: 4109364224
Parameters: 68012160
Training Data: ImageNet-1k
In Collection: MoCoV3
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/mocov3_resnet50_8xb512-amp-coslr-800e_in1k_20220927-e043f51a.pth
Config: configs/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k.py
Downstream:
- resnet50_mocov3-800e-pre_8xb128-linear-coslr-90e_in1k
- Name: resnet50_mocov3-100e-pre_8xb128-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 1024
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 69.6
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-8f7d937e.pth
Config: configs/mocov3/benchmarks/resnet50_8xb128-linear-coslr-90e_in1k.py
- Name: resnet50_mocov3-300e-pre_8xb128-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 1024
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 72.8
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-d21ddac2.pth
Config: configs/mocov3/benchmarks/resnet50_8xb128-linear-coslr-90e_in1k.py
- Name: resnet50_mocov3-800e-pre_8xb128-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 1024
FLOPs: 4109464576
Parameters: 25557032
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 74.4
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-0e97a483.pth
Config: configs/mocov3/benchmarks/resnet50_8xb128-linear-coslr-90e_in1k.py
- Name: mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k
Metadata:
Epochs: 300
Batch Size: 4096
FLOPs: 4607954304
Parameters: 84266752
Training Data: ImageNet-1k
In Collection: MoCoV3
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k-224_20220826-08bc52f7.pth
Config: configs/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k.py
Downstream:
- vit-small-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
- Name: vit-small-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 1024
FLOPs: 4607954304
Parameters: 22050664
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 73.6
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k_20220826-376674ef.pth
Config: configs/mocov3/benchmarks/vit-small-p16_8xb128-linear-coslr-90e_in1k.py
- Name: mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k
Metadata:
Epochs: 300
Batch Size: 4096
FLOPs: 17581972224
Parameters: 215678464
Training Data: ImageNet-1k
In Collection: MoCoV3
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k-224_20220826-25213343.pth
Config: configs/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k.py
Downstream:
- vit-base-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
- vit-base-p16_mocov3-pre_8xb64-coslr-150e_in1k
- Name: vit-base-p16_mocov3-pre_8xb64-coslr-150e_in1k
Metadata:
Epochs: 150
Batch Size: 512
FLOPs: 17581972224
Parameters: 86567656
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 83.0
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k_20220826-f1e6c442.pth
Config: configs/mocov3/benchmarks/vit-base-p16_8xb64-coslr-150e_in1k.py
- Name: vit-base-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
Metadata:
Epochs: 90
Batch Size: 1024
FLOPs: 17581972224
Parameters: 86567656
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 76.9
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k_20220826-83be7758.pth
Config: configs/mocov3/benchmarks/vit-base-p16_8xb128-linear-coslr-90e_in1k.py
- Name: mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k
Metadata:
Epochs: 300
Batch Size: 4096
FLOPs: 61603111936
Parameters: 652781568
Training Data: ImageNet-1k
In Collection: MoCoV3
Results: null
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k-224_20220829-9b88a442.pth
Config: configs/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k.py
Downstream:
- vit-large-p16_mocov3-pre_8xb64-coslr-100e_in1k
- Name: vit-large-p16_mocov3-pre_8xb64-coslr-100e_in1k
Metadata:
Epochs: 100
Batch Size: 512
FLOPs: 61603111936
Parameters: 304326632
Training Data: ImageNet-1k
In Collection: MoCoV3
Results:
- Task: Image Classification
Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 83.7
Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k_20220829-878a2f7f.pth
Config: configs/mocov3/benchmarks/vit-large-p16_8xb64-coslr-100e_in1k.py
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