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metafile.yml
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Collections:
- Name: DeiT
Metadata:
Training Data: ImageNet-1k
Architecture:
- Layer Normalization
- Scaled Dot-Product Attention
- Attention Dropout
- Multi-Head Attention
Paper:
Title: Training data-efficient image transformers & distillation through attention
URL: https://arxiv.org/abs/2012.12877
README: configs/deit/README.md
Code:
URL: v0.19.0
Version: https://github.com/open-mmlab/mmpretrain/blob/v0.19.0/mmcls/models/backbones/deit.py
Models:
- Name: deit-tiny_4xb256_in1k
Metadata:
FLOPs: 1258219200
Parameters: 5717416
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 74.5
Top 5 Accuracy: 92.24
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-tiny_pt-4xb256_in1k_20220218-13b382a0.pth
Config: configs/deit/deit-tiny_4xb256_in1k.py
- Name: deit-tiny-distilled_3rdparty_in1k
Metadata:
FLOPs: 1265371776
Parameters: 5910800
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 74.51
Top 5 Accuracy: 91.9
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-tiny-distilled_3rdparty_pt-4xb256_in1k_20211216-c429839a.pth
Config: configs/deit/deit-tiny-distilled_4xb256_in1k.py
Converted From:
Weights: https://dl.fbaipublicfiles.com/deit/deit_tiny_distilled_patch16_224-b40b3cf7.pth
Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L108
- Name: deit-small_4xb256_in1k
Metadata:
FLOPs: 4607954304
Parameters: 22050664
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 80.69
Top 5 Accuracy: 95.06
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-small_pt-4xb256_in1k_20220218-9425b9bb.pth
Config: configs/deit/deit-small_4xb256_in1k.py
- Name: deit-small-distilled_3rdparty_in1k
Metadata:
FLOPs: 4632876288
Parameters: 22436432
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 81.17
Top 5 Accuracy: 95.4
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-small-distilled_3rdparty_pt-4xb256_in1k_20211216-4de1d725.pth
Config: configs/deit/deit-small-distilled_4xb256_in1k.py
Converted From:
Weights: https://dl.fbaipublicfiles.com/deit/deit_small_distilled_patch16_224-649709d9.pth
Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L123
- Name: deit-base_16xb64_in1k
Metadata:
FLOPs: 17581972224
Parameters: 86567656
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 81.76
Top 5 Accuracy: 95.81
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_pt-16xb64_in1k_20220216-db63c16c.pth
Config: configs/deit/deit-base_16xb64_in1k.py
- Name: deit-base_3rdparty_in1k
Metadata:
FLOPs: 17581972224
Parameters: 86567656
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 81.79
Top 5 Accuracy: 95.59
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_pt-16xb64_in1k_20211124-6f40c188.pth
Config: configs/deit/deit-base_16xb64_in1k.py
Converted From:
Weights: https://dl.fbaipublicfiles.com/deit/deit_base_patch16_224-b5f2ef4d.pth
Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L93
- Name: deit-base-distilled_3rdparty_in1k
Metadata:
FLOPs: 17674283520
Parameters: 87338192
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 83.33
Top 5 Accuracy: 96.49
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_pt-16xb64_in1k_20211216-42891296.pth
Config: configs/deit/deit-base-distilled_16xb64_in1k.py
Converted From:
Weights: https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_224-df68dfff.pth
Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L138
- Name: deit-base_224px-pre_3rdparty_in1k-384px
Metadata:
FLOPs: 55538974464
Parameters: 86859496
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 83.04
Top 5 Accuracy: 96.31
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_ft-16xb32_in1k-384px_20211124-822d02f2.pth
Config: configs/deit/deit-base_16xb32_in1k-384px.py
Converted From:
Weights: https://dl.fbaipublicfiles.com/deit/deit_base_patch16_384-8de9b5d1.pth
Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L153
- Name: deit-base-distilled_224px-pre_3rdparty_in1k-384px
Metadata:
FLOPs: 55645294080
Parameters: 87630032
In Collection: DeiT
Results:
- Dataset: ImageNet-1k
Metrics:
Top 1 Accuracy: 85.55
Top 5 Accuracy: 97.35
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_ft-16xb32_in1k-384px_20211216-e48d6000.pth
Config: configs/deit/deit-base-distilled_16xb32_in1k-384px.py
Converted From:
Weights: https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_384-d0272ac0.pth
Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L168