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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
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