metafile.yml 6.0 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153
  1. Collections:
  2. - Name: DeiT
  3. Metadata:
  4. Training Data: ImageNet-1k
  5. Architecture:
  6. - Layer Normalization
  7. - Scaled Dot-Product Attention
  8. - Attention Dropout
  9. - Multi-Head Attention
  10. Paper:
  11. Title: Training data-efficient image transformers & distillation through attention
  12. URL: https://arxiv.org/abs/2012.12877
  13. README: configs/deit/README.md
  14. Code:
  15. URL: v0.19.0
  16. Version: https://github.com/open-mmlab/mmpretrain/blob/v0.19.0/mmcls/models/backbones/deit.py
  17. Models:
  18. - Name: deit-tiny_4xb256_in1k
  19. Metadata:
  20. FLOPs: 1258219200
  21. Parameters: 5717416
  22. In Collection: DeiT
  23. Results:
  24. - Dataset: ImageNet-1k
  25. Metrics:
  26. Top 1 Accuracy: 74.5
  27. Top 5 Accuracy: 92.24
  28. Task: Image Classification
  29. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-tiny_pt-4xb256_in1k_20220218-13b382a0.pth
  30. Config: configs/deit/deit-tiny_4xb256_in1k.py
  31. - Name: deit-tiny-distilled_3rdparty_in1k
  32. Metadata:
  33. FLOPs: 1265371776
  34. Parameters: 5910800
  35. In Collection: DeiT
  36. Results:
  37. - Dataset: ImageNet-1k
  38. Metrics:
  39. Top 1 Accuracy: 74.51
  40. Top 5 Accuracy: 91.9
  41. Task: Image Classification
  42. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-tiny-distilled_3rdparty_pt-4xb256_in1k_20211216-c429839a.pth
  43. Config: configs/deit/deit-tiny-distilled_4xb256_in1k.py
  44. Converted From:
  45. Weights: https://dl.fbaipublicfiles.com/deit/deit_tiny_distilled_patch16_224-b40b3cf7.pth
  46. Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L108
  47. - Name: deit-small_4xb256_in1k
  48. Metadata:
  49. FLOPs: 4607954304
  50. Parameters: 22050664
  51. In Collection: DeiT
  52. Results:
  53. - Dataset: ImageNet-1k
  54. Metrics:
  55. Top 1 Accuracy: 80.69
  56. Top 5 Accuracy: 95.06
  57. Task: Image Classification
  58. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-small_pt-4xb256_in1k_20220218-9425b9bb.pth
  59. Config: configs/deit/deit-small_4xb256_in1k.py
  60. - Name: deit-small-distilled_3rdparty_in1k
  61. Metadata:
  62. FLOPs: 4632876288
  63. Parameters: 22436432
  64. In Collection: DeiT
  65. Results:
  66. - Dataset: ImageNet-1k
  67. Metrics:
  68. Top 1 Accuracy: 81.17
  69. Top 5 Accuracy: 95.4
  70. Task: Image Classification
  71. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-small-distilled_3rdparty_pt-4xb256_in1k_20211216-4de1d725.pth
  72. Config: configs/deit/deit-small-distilled_4xb256_in1k.py
  73. Converted From:
  74. Weights: https://dl.fbaipublicfiles.com/deit/deit_small_distilled_patch16_224-649709d9.pth
  75. Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L123
  76. - Name: deit-base_16xb64_in1k
  77. Metadata:
  78. FLOPs: 17581972224
  79. Parameters: 86567656
  80. In Collection: DeiT
  81. Results:
  82. - Dataset: ImageNet-1k
  83. Metrics:
  84. Top 1 Accuracy: 81.76
  85. Top 5 Accuracy: 95.81
  86. Task: Image Classification
  87. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_pt-16xb64_in1k_20220216-db63c16c.pth
  88. Config: configs/deit/deit-base_16xb64_in1k.py
  89. - Name: deit-base_3rdparty_in1k
  90. Metadata:
  91. FLOPs: 17581972224
  92. Parameters: 86567656
  93. In Collection: DeiT
  94. Results:
  95. - Dataset: ImageNet-1k
  96. Metrics:
  97. Top 1 Accuracy: 81.79
  98. Top 5 Accuracy: 95.59
  99. Task: Image Classification
  100. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_pt-16xb64_in1k_20211124-6f40c188.pth
  101. Config: configs/deit/deit-base_16xb64_in1k.py
  102. Converted From:
  103. Weights: https://dl.fbaipublicfiles.com/deit/deit_base_patch16_224-b5f2ef4d.pth
  104. Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L93
  105. - Name: deit-base-distilled_3rdparty_in1k
  106. Metadata:
  107. FLOPs: 17674283520
  108. Parameters: 87338192
  109. In Collection: DeiT
  110. Results:
  111. - Dataset: ImageNet-1k
  112. Metrics:
  113. Top 1 Accuracy: 83.33
  114. Top 5 Accuracy: 96.49
  115. Task: Image Classification
  116. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_pt-16xb64_in1k_20211216-42891296.pth
  117. Config: configs/deit/deit-base-distilled_16xb64_in1k.py
  118. Converted From:
  119. Weights: https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_224-df68dfff.pth
  120. Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L138
  121. - Name: deit-base_224px-pre_3rdparty_in1k-384px
  122. Metadata:
  123. FLOPs: 55538974464
  124. Parameters: 86859496
  125. In Collection: DeiT
  126. Results:
  127. - Dataset: ImageNet-1k
  128. Metrics:
  129. Top 1 Accuracy: 83.04
  130. Top 5 Accuracy: 96.31
  131. Task: Image Classification
  132. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_ft-16xb32_in1k-384px_20211124-822d02f2.pth
  133. Config: configs/deit/deit-base_16xb32_in1k-384px.py
  134. Converted From:
  135. Weights: https://dl.fbaipublicfiles.com/deit/deit_base_patch16_384-8de9b5d1.pth
  136. Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L153
  137. - Name: deit-base-distilled_224px-pre_3rdparty_in1k-384px
  138. Metadata:
  139. FLOPs: 55645294080
  140. Parameters: 87630032
  141. In Collection: DeiT
  142. Results:
  143. - Dataset: ImageNet-1k
  144. Metrics:
  145. Top 1 Accuracy: 85.55
  146. Top 5 Accuracy: 97.35
  147. Task: Image Classification
  148. Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_ft-16xb32_in1k-384px_20211216-e48d6000.pth
  149. Config: configs/deit/deit-base-distilled_16xb32_in1k-384px.py
  150. Converted From:
  151. Weights: https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_384-d0272ac0.pth
  152. Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L168