mmpretrain/configs/t2t_vit/metafile.yml

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YAML

Collections:
- Name: Tokens-to-Token ViT
Metadata:
Training Data: ImageNet-1k
Architecture:
- Layer Normalization
- Scaled Dot-Product Attention
- Attention Dropout
- Dropout
- Tokens to Token
Paper:
URL: https://arxiv.org/abs/2101.11986
Title: "Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet"
README: configs/t2t_vit/README.md
Code:
URL: https://github.com/open-mmlab/mmpretrain/blob/v0.17.0/mmcls/models/backbones/t2t_vit.py
Version: v0.17.0
Models:
- Name: t2t-vit-t-14_8xb64_in1k
Metadata:
FLOPs: 4340000000
Parameters: 21470000
In Collection: Tokens-to-Token ViT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 81.83
Top 5 Accuracy: 95.84
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-14_8xb64_in1k_20211220-f7378dd5.pth
Config: configs/t2t_vit/t2t-vit-t-14_8xb64_in1k.py
- Name: t2t-vit-t-19_8xb64_in1k
Metadata:
FLOPs: 7800000000
Parameters: 39080000
In Collection: Tokens-to-Token ViT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 82.63
Top 5 Accuracy: 96.18
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-19_8xb64_in1k_20211214-7f5e3aaf.pth
Config: configs/t2t_vit/t2t-vit-t-19_8xb64_in1k.py
- Name: t2t-vit-t-24_8xb64_in1k
Metadata:
FLOPs: 12690000000
Parameters: 64000000
In Collection: Tokens-to-Token ViT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 82.71
Top 5 Accuracy: 96.09
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-24_8xb64_in1k_20211214-b2a68ae3.pth
Config: configs/t2t_vit/t2t-vit-t-24_8xb64_in1k.py