mmselfsup/docs/en/model_zoo.md

Model Zoo

All models and part of benchmark results are recorded below.

• Model Zoo
  • Statistics
  • Benchmarks
    • ImageNet

Statistics

• Number of papers: 17

• Number of checkpoints: 60

Benchmarks

ImageNet

ImageNet has multiple versions, but the most commonly used one is ILSVRC 2012. The classification results below are reported by linear evaluation or fine-tuning with pre-trained weights provided by various algorithms.

Algorithm	Backbone	Epoch	Batch Size	Results (Top-1 %)		Links
				Linear Eval	Fine-tuning	Pretrain	Linear Eval	Fine-tuning
Relative-Loc	ResNet50	70	512	40.4	/	config | model | log	config | model | log	/
Rotation-Pred	ResNet50	70	128	47.0	/	config | model | log	config | model | log	/
NPID	ResNet50	200	256	58.3	/	config | model | log	config | model | log	/
SimCLR	ResNet50	200	256	62.7	/	config | model | log	config | model | log	/
	ResNet50	200	4096	66.9	/	config | model | log	config | model | log	/
	ResNet50	800	4096	69.2	/	config | model | log	config | model | log	/
MoCo v2	ResNet50	200	256	67.5	/	config | model | log	config | model | log	/
BYOL	ResNet50	200	4096	71.8	/	config | model | log	config | model | log	/
SwAV	ResNet50	200	256	70.5	/	config | model | log	config | model | log	/
DenseCL	ResNet50	200	256	63.5	/	config | model | log	config | model | log	/
SimSiam	ResNet50	100	256	68.3	/	config | model | log	config | model | log	/
	ResNet50	200	256	69.8	/	config | model | log	config | model | log	/
BarlowTwins	ResNet50	300	2048	71.8	/	config | model | log	config | model | log	/
MoCo v3	ResNet50	100	4096	69.6	/	config | model | log	config | model | log	/
	ResNet50	300	4096	72.8	/	config | model | log	config | model | log	/
	ResNet50	800	4096	74.4	/	config | model | log	config | model | log	/
	ViT-small	300	4096	73.6	/	config | model | log	config | model | log	/
	ViT-base	300	4096	76.9	83.0	config | model | log	config | model | log	config | model | log
	ViT-large	300	4096	/	83.7	config | model | log	/	config | model | log
MAE	ViT-base	300	4096	60.8	83.1	config | model | log	config | model | log	config | model | log
	ViT-base	400	4096	62.5	83.3	config | model | log	config | model | log	config | model | log
	ViT-base	800	4096	65.1	83.3	config | model | log	config | model | log	config | model | log
	ViT-base	1600	4096	67.1	83.5	config | model | log	config | model | log	config | model | log
	ViT-large	400	4096	70.7	85.2	config | model | log	config | model | log	config | model | log
	ViT-large	800	4096	73.7	85.4	config | model | log	config | model | log	config | model | log
	ViT-large	1600	4096	75.5	85.7	config | model | log	config | model | log	config | model | log
	ViT-huge-FT-224	1600	4096	/	86.9	config | model | log	/	config | model | log
	ViT-huge-FT-448	1600	4096	/	87.3	config | model | log	/	config | model | log
CAE	ViT-base	300	2048	/	83.3	config | model | log	/	config | model | log
SimMIM	Swin-base-FT192	100	2048	/	82.7	config | model | log	/	config | model | log
	Swin-base-FT224	100	2048	/	83.5	config | model | log	/	config | model | log
	Swin-base-FT224	800	2048	/	83.8	config | model | log	/	config | model | log
	Swin-large-FT224	800	2048	/	84.8	config | model | log	/	config | model | log