mmpretrain/configs/van/metafile.yml

71 lines
2.4 KiB
YAML

Collections:
- Name: Visual-Attention-Network
Metadata:
Training Data: ImageNet-1k
Training Techniques:
- AdamW
- Weight Decay
Architecture:
- Visual Attention Network
Paper:
URL: https://arxiv.org/pdf/2202.09741v2.pdf
Title: "Visual Attention Network"
README: configs/van/README.md
Code:
URL: https://github.com/open-mmlab/mmclassification/blob/v0.23.0/mmcls/models/backbones/van.py
Version: v0.23.0
Models:
- Name: van-tiny_8xb128_in1k
Metadata:
FLOPs: 4110000 # 4.11M
Parameters: 880000000 # 0.88G
In Collection: Visual-Attention-Network
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 75.41
Top 5 Accuracy: 93.02
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/van/van-tiny_8xb128_in1k_20220427-8ac0feec.pth
Config: configs/van/van-tiny_8xb128_in1k.py
- Name: van-small_8xb128_in1k
Metadata:
FLOPs: 13860000 # 13.86M
Parameters: 2520000000 # 2.52G
In Collection: Visual-Attention-Network
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 81.01
Top 5 Accuracy: 95.63
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/van/van-small_8xb128_in1k_20220427-bd6a9edd.pth
Config: configs/van/van-small_8xb128_in1k.py
- Name: van-base_8xb128_in1k
Metadata:
FLOPs: 26580000 # 26.58M
Parameters: 5030000000 # 5.03G
In Collection: Visual-Attention-Network
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 82.80
Top 5 Accuracy: 96.21
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/van/van-base_8xb128_in1k_20220427-5275471d.pth
Config: configs/van/van-base_8xb128_in1k.py
- Name: van-large_8xb128_in1k
Metadata:
FLOPs: 44770000 # 44.77 M
Parameters: 8990000000 # 8.99G
In Collection: Visual-Attention-Network
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 83.86
Top 5 Accuracy: 96.73
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/van/van-large_8xb128_in1k_20220427-56159105.pth
Config: configs/van/van-large_8xb128_in1k.py