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159b38d276
* Add cosine cool down lr updater * Use ema hook * Update decay mult * Update configs. * Update T2T-ViT readme and format all readme * Update swin readme * Update tnt readme * Add docstring for `CosineAnnealingCooldownLrUpdaterHook`. * Update t2t readme and metafile
59 lines
1.9 KiB
YAML
59 lines
1.9 KiB
YAML
Collections:
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- Name: Tokens-to-Token ViT
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Metadata:
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Training Data: ImageNet-1k
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Architecture:
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- Layer Normalization
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- Scaled Dot-Product Attention
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- Attention Dropout
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- Dropout
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- Tokens to Token
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Paper:
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URL: https://arxiv.org/abs/2101.11986
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Title: "Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet"
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README: configs/t2t_vit/README.md
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Code:
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URL: https://github.com/open-mmlab/mmclassification/blob/v0.17.0/mmcls/models/backbones/t2t_vit.py
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Version: v0.17.0
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Models:
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- Name: t2t-vit-t-14_8xb64_in1k
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Metadata:
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FLOPs: 4340000000
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Parameters: 21470000
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In Collection: Tokens-to-Token ViT
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 81.83
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Top 5 Accuracy: 95.84
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-14_8xb64_in1k_20211220-f7378dd5.pth
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Config: configs/t2t_vit/t2t-vit-t-14_8xb64_in1k.py
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- Name: t2t-vit-t-19_8xb64_in1k
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Metadata:
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FLOPs: 7800000000
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Parameters: 39080000
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In Collection: Tokens-to-Token ViT
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 82.63
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Top 5 Accuracy: 96.18
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-19_8xb64_in1k_20211214-7f5e3aaf.pth
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Config: configs/t2t_vit/t2t-vit-t-19_8xb64_in1k.py
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- Name: t2t-vit-t-24_8xb64_in1k
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Metadata:
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FLOPs: 12690000000
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Parameters: 64000000
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In Collection: Tokens-to-Token ViT
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 82.71
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Top 5 Accuracy: 96.09
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-24_8xb64_in1k_20211214-b2a68ae3.pth
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Config: configs/t2t_vit/t2t-vit-t-24_8xb64_in1k.py
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