mmselfsup/docs/en/model_zoo.md

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2021-12-15 19:06:36 +08:00
# Model Zoo
All models and part of benchmark results are recorded below.
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- [Model Zoo](#model-zoo)
- [Benchmarks](#benchmarks)
- [ImageNet](#imagenet)
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## Benchmarks
### ImageNet
Bump version to v0.7.0 (#229) * [Enhance] add pre-commit hook for algo-readme and copyright (#213) * [Enhance] add test windows in workflows (#215) * [Enhance] add test windows in workflows * fix lint * add optional requirements * add try-except judgement * add opencv installation in windows test steps * fix path error on windows * update * update path * update * add pytest skip for algorithm test * update requirements/runtime.txt * update pytest skip * [Docs] translate 0_config.md into Chinese (#216) * [Docs] translate 0_config.md into Chinese * [Fix] fix format description in 0_config.md * Update: 0_config.md * [Fix] fix tsne 'no `init_cfg`' error (#222) * [Fix] fix tsne 'no init_cfg' and pool_type errors * [Refactor] fix linting of tsne vis * [Docs] reorganizing OpenMMLab projects and update algorithms in readme (#219) * [Docs] reorganizing OpenMMLab projects and update algorithms in readme * using small letters * fix typo * [Fix] fix image channel bgr/rgb bug and update benchmarks (#210) * [Fix] fix image channel bgr/rgb bug * update model zoo * update readme and metafile * [Fix] fix typo * [Fix] fix typo * [Fix] fix lint * modify Places205 directory according to the downloaded dataset * update results * [Fix] Fix the bug when using prefetch under multi-view methods, e.g., DenseCL (#218) * fig bug for prefetch_loader under multi-view setting * fix lint problem Co-authored-by: liming <liming.ai@bytedance.com> * [Feature]: MAE official (#221) * [Feature]: MAE single image pre-training * [Fix]: Fix config * [Fix]: Fix dataset link * [Feature]: Add run * [Refactor]: Delete spot * [Feature]: ignore nohup output file * [Feature]: Add auto script to generate run cmd * [Refactor]: Refactor mae config file * [Feature]: sz20 settings * [Feature]: Add auto resume * [Fix]: Fix lint * [Feature]: Make git ignore txt * [Refactor]: Delete gpus in script * [Fix]: Make generate_cmd to add --async * [Feature]: Initial version of Vit fine-tune * [Fix]: Add 1424 specific settings * [Fix]: Fix missing file client bug for 1424 * [Feature]: 1424 customized settings * [Fix]: Make drop in eval to False * [Feature]: Change the finetune and pre-training settings * [Feature]: Add debug setting * [Refactor]: Refactor the model * [Feature]: Customized settings * [Feature]: Add A100 settings * [Fix]: Change mae to imagenet * [Feature]: Change mae pretrain num workers to 32 * [Feature]: Change num workers to 16 * [Feature]: Add A100 setting for pre_release ft version * [Feature]: Add img_norm_cfg * [Fix]: Fix mae cls test missing logits bug * [Fix]: Fix mae cls head bias initialize to zero * [Feature]: Rename mae config name * [Feature]: Add MAE README.md * [Fix]: Fix lint * [Feature]: Fix typo * [Fix]: Fix typo * [Feature]: Fix invalid link * [Fix]: Fix finetune config file name * [Feature]: Official pretrain v1 * [Feature]: Change log interval to 100 * [Feature]: pretrain 1600 epochs * [Fix]: Change encoder num head to 12 * [Feature]: Mix precision * [Feature]: Add default value to random masking * [Feature]: Official MAE finetune * [Feature]: Finetune img per gpu 32 * [Feature]: Add multi machine training for lincls * [Fix]: Fix lincls master port master addr * [Feature]: Change img per gpu to 128 * [Feature]: Add linear eval and Refactor * [Fix]: Fix debug mode * [Fix]: Delete MAE dataset in __init__.py * [Feature]: normalize pixel for mae * [Fix]: Fix lint * [Feature]: LARS for linear eval * [Feature]: Add lars for mae linear eval * [Feature]: Change mae linear lars num workers to 32 * [Feature]: Change mae linear lars num workers to 8 * [Feature]: log every 25 iter for mae linear eval lars * [Feature]: Add 1600 epoch and 800 epoch pretraining * [Fix]: Change linear eval to 902 * [Fix]: Add random flip to linear eval * [Fix]: delete fp16 in mae * [Refactor]: Change backbone to mmcls * [Fix]: Align finetune settings * [Fix]: replace timm trunc_normal with mmcv trunc_normal * [Fix]: Change finetune layer_decay to 0.65 * [Fix]: Delete pretrain last norm when global_pooling * [Fix]: set requires_grad of norm1 to False * [Fix]: delete norm1 * [Fix]: Fix docstring bug * [Fix]: Fix lint * [Fix]: Add external link * [Fix]: Delete auto_resume and reformat config readme. * [Fix]: Fix pytest bug * [Fix]: Fix lint * [Refactor]: Rename filename * [Feature]: Add docstring * [Fix]: Rename config file name * [Fix]: Fix name inconsistency bug * [Fix]: Change the default value of persistent_worker in builder to True * [Fix]: Change the default value of CPUS_PER_TASK to 5 * [Fix]: Add a blank line to line136 in tools/train.py * [Fix]: Fix MAE algorithm docstring format and add paper name and url * [Feature]: Add MAE paper name and link, and store mae teaser on github * [Refactor]: Delete mae.png * [Fix]: Fix config file name” * [Fix]: Fix name bug * [Refactor]: Change default GPUS to 8 * [Fix]: Abandon change to drop_last * [Fix]: Fix docstring in mae algorithm * [Fix]: Fix lint * [Fix]: Fix lint * [Fix]: Fix mae finetune algo type bug * [Feature]: Add unit test for algorithm * [Feature]: Add unit test for remaining parts * [Fix]: Fix lint * [Fix]: Fix typo * [Fix]: Delete some unnecessary modification in gitignore * [Feature]: Change finetune setting in mae algo to mixup setting * [Fix]: Change norm_pix_loss to norm_pix in pretrain head * [Fix]: Delete modification in dist_train_linear.sh * [Refactor]: Delete global pool in mae_cls_vit.py * [Fix]: Change finetune param to mixup in test_mae_classification * [Fix]: Change norm_pix_loss to norm_pix of mae_pretrain_head in unit test * [Fix]: Change norm_pix_loss to norm_pix in unit test * [Refactor]: Create init_weights for mae_finetune_head and mae_linprobe_head * [Refactor]: Construct 2d sin-cosine position embedding using torch * [Refactor]: Using classification and using mixup from mmcls * [Fix]: Fix lint * [Fix]: Add False to finetune mae linprobe‘ “ * [Fix]: Set drop_last to False * [Fix]: Fix MAE finetune layerwise lr bug * [Refactor]: Delete redundant MAE when registering MAE * [Refactor]: Split initialize_weights in MAE to submodules * [Fix]: Change the min_lr of mae pretrain to 0.0 * [Refactor]: Delete unused _init_weights in mae_cls_vit * [Refactor]: Change MAE cls vit to a more general name * [Feature]: Add Epoch Fix cosine annealing lr updater * [Fix]: Fix lint * [Feature]: Add layer wise lr decay in optimizer constructor * [Fix]: Fix lint * [Fix]: Fix set layer wise lr decay bug * [Fix]: Fix UT for MAE * [Fix]: Fix lint * [Fix]: update algorithm readme format for MAE * [Fix]: Fix isort * [Fix]: Add Returns inmae_pretrain_vit * [Fix]: Change bgr to rgb * [Fix]: Change norm pix to True * [Fix]: Use cls_token to linear prob * [Fix]: Delete mixup.py * [Fix]: Fix MAE readme * [Feature]: Delete linprobe * [Refactor]: Merge MAE head into one file * [Fix]: Fix lint * [Fix]: rename mae_pretrain_head to mae_head * [Fix]: Fix import error in __init__.py * [Feature]: skip MAE algo UT when running on windows * [Fix]: Fix UT bug * [Feature]: Update model_zoo * [Fix]: Rename MAE pretrain model name * [Fix]: Delete mae ft prefix * [Feature]: Change b to base * [Refactor]: Change b in MAE pt config to base * [Fix]: Fix typo in docstring * [Fix]: Fix name bug * [Feature]: Add new constructor for MAE finetune * [Fix]: Fix model_zoo link * [Fix]: Skip UT for MAE * [Fix]: Change fixed channel order to param Co-authored-by: LIU Yuan <liuyuuan@pjlab.org.cn> Co-authored-by: liu yuan <liuyuan@pjlab.org.cn> * [Feature]: Add diff seeds to diff ranks and set torch seed in worker_init_fn (#228) * [Feature]: Add set diff seeds to diff ranks * [Fix]: Set diff seed to diff workers * Bump version to v0.7.0 (#227) * Bump version to v0.7.0 * [Docs] update readme Co-authored-by: wang11wang <95845452+wang11wang@users.noreply.github.com> Co-authored-by: Liangyu Chen <45140242+c-liangyu@users.noreply.github.com> Co-authored-by: Ming Li <73068772+mitming@users.noreply.github.com> Co-authored-by: liming <liming.ai@bytedance.com> Co-authored-by: Yuan Liu <30762564+YuanLiuuuuuu@users.noreply.github.com> Co-authored-by: LIU Yuan <liuyuuan@pjlab.org.cn> Co-authored-by: liu yuan <liuyuan@pjlab.org.cn>
2022-03-04 13:43:49 +08:00
ImageNet has multiple versions, but the most commonly used one is ILSVRC 2012. The classification results below are reported by linear evaluation or fine-tuning with pre-trained weights provided by various algorithms.
Bump version to v0.9.1 (#322) * [Fix]: Set qkv bias to False for cae and True for mae (#303) * [Fix]: Add mmcls transformer layer choice * [Fix]: Fix transformer encoder layer bug * [Fix]: Change UT of cae * [Feature]: Change the file name of cosine annealing hook (#304) * [Feature]: Change cosine annealing hook file name * [Feature]: Add UT for cosine annealing hook * [Fix]: Fix lint * read tutorials and fix typo (#308) * [Fix] fix config errors in MAE (#307) * update readthedocs algorithm readme (#310) * [Docs] Replace markdownlint with mdformat (#311) * Replace markdownlint with mdformat to avoid installing ruby * fix typo * add 'ba' to codespell ignore-words-list * Configure Myst-parser to parse anchor tag (#309) * [Docs] rewrite install.md (#317) * rewrite the install.md * add faq.md * fix lint * add FAQ to README * add Chinese version * fix typo * fix format * remove modification * fix format * [Docs] refine README.md file (#318) * refine README.md file * fix lint * format language button * rename getting_started.md * revise index.rst * add model_zoo.md to index.rst * fix lint * refine readme Co-authored-by: Jiahao Xie <52497952+Jiahao000@users.noreply.github.com> * [Enhance] update byol models and results (#319) * Update version information (#321) Co-authored-by: Yuan Liu <30762564+YuanLiuuuuuu@users.noreply.github.com> Co-authored-by: Yi Lu <21515006@zju.edu.cn> Co-authored-by: RenQin <45731309+soonera@users.noreply.github.com> Co-authored-by: Jiahao Xie <52497952+Jiahao000@users.noreply.github.com>
2022-06-01 09:59:05 +08:00
<table class="docutils">
<thead>
<tr>
<th rowspan="2">Algorithm</th>
<th rowspan="2">Backbone</th>
<th rowspan="2">Epoch</th>
<th rowspan="2">Batch Size</th>
<th colspan="2" align="center">Results (Top-1 %)</th>
<th colspan="3" align="center">Links</th>
</tr>
<tr>
<th>Linear Eval</th>
<th>Fine-tuning</th>
<th>Pretrain</th>
<th>Linear Eval</th>
<th>Fine-tuning</th>
</tr>
</thead>
<tbody>
<tr>
<td>Relative-Loc</td>
<td>ResNet50</td>
<td>70</td>
<td>512</td>
<td>40.4</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220825-daae1b41.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220802_223045.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-c2a0b188.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220804_194226.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>Rotation-Pred</td>
<td>ResNet50</td>
<td>70</td>
<td>128</td>
<td>47.0</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220825-a8bf5f69.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220805_113136.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-7c6edcb3.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220808_143921.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>NPID</td>
<td>ResNet50</td>
<td>200</td>
<td>256</td>
<td>58.3</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/npid_resnet50_8xb32-steplr-200e_in1k_20220825-a67c5440.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/npid_resnet50_8xb32-steplr-200e_in1k_20220725_161221.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-661b736e.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/npid/npid_resnet50_8xb32-steplr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220728_150535.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td rowspan="3">SimCLR</td>
<td>ResNet50</td>
<td>200</td>
<td>256</td>
<td>62.7</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/simclr_resnet50_8xb32-coslr-200e_in1k_20220825-15f807a4.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/simclr_resnet50_8xb32-coslr-200e_in1k_20220721_103223.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-9596a505.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220724_210050.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ResNet50</td>
<td>200</td>
<td>4096</td>
<td>66.9</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/simclr_resnet50_16xb256-coslr-200e_in1k_20220825-4d9cce50.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/simclr_resnet50_16xb256-coslr-200e_in1k_20220721_150508.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-f12c0457.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220724_172050.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ResNet50</td>
<td>800</td>
<td>4096</td>
<td>69.2</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/simclr_resnet50_16xb256-coslr-800e_in1k_20220825-85fcc4de.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/simclr_resnet50_16xb256-coslr-800e_in1k_20220725_112248.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-b80ae1e5.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simclr/simclr_resnet50_16xb256-coslr-800e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220730_165101.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>MoCo v2</td>
<td>ResNet50</td>
<td>200</td>
<td>256</td>
<td>67.5</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/mocov2_resnet50_8xb32-coslr-200e_in1k_20220825-b6d23c86.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/mocov2_resnet50_8xb32-coslr-200e_in1k_20220721_215805.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-994c4128.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220724_172046.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>BYOL</td>
<td>ResNet50</td>
<td>200</td>
<td>4096</td>
<td>71.8</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/byol_resnet50_16xb256-coslr-200e_in1k_20220825-de817331.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/byol_resnet50_16xb256-coslr-200e_in1k_20220721_150515.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-7596c6f5.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/byol/byol_resnet50_16xb256-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220724_130251.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>SwAV</td>
<td>ResNet50</td>
<td>200</td>
<td>256</td>
<td>70.5</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220825-5b3fc7fc.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20220728_141003.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220825-80341e08.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220802_145230.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>DenseCL</td>
<td>ResNet50</td>
<td>200</td>
<td>256</td>
<td>63.5</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/densecl_resnet50_8xb32-coslr-200e_in1k_20220825-3078723b.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/densecl_resnet50_8xb32-coslr-200e_in1k_20220727_221415.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-steplr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-f0f0a579.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/densecl/densecl_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220730_091650.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td rowspan="2">SimSiam</td>
<td>ResNet50</td>
<td>100</td>
<td>256</td>
<td>68.3</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/simsiam_resnet50_8xb32-coslr-100e_in1k_20220825-d07cb2e6.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/simsiam_resnet50_8xb32-coslr-100e_in1k_20220725_224724.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-f53ba400.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220804_175115.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ResNet50</td>
<td>200</td>
<td>256</td>
<td>69.8</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/simsiam_resnet50_8xb32-coslr-200e_in1k_20220825-efe91299.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/simsiam_resnet50_8xb32-coslr-200e_in1k_20220726_033722.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb512-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220825-519b5135.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb512-coslr-90e_in1k/resnet50_linear-8xb512-coslr-90e_in1k_20220802_120717.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>BarlowTwins</td>
<td>ResNet50</td>
<td>300</td>
<td>2048</td>
<td>71.8</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/barlowtwins_resnet50_8xb256-coslr-300e_in1k_20220825-57307488.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/barlowtwins_resnet50_8xb256-coslr-300e_in1k_20220726_033718.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb32-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220825-52fde35f.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k/resnet50_linear-8xb32-coslr-100e_in1k/resnet50_linear-8xb32-coslr-100e_in1k_20220730_093018.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td rowspan="6">MoCo v3</td>
<td>ResNet50</td>
<td>100</td>
<td>4096</td>
<td>69.6</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/mocov3_resnet50_8xb512-amp-coslr-100e_in1k_20220927-f1144efa.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/mocov3_resnet50_8xb512-amp-coslr-100e_in1k_20220915_154635.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-8f7d937e.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220920_113350.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ResNet50</td>
<td>300</td>
<td>4096</td>
<td>72.8</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/mocov3_resnet50_8xb512-amp-coslr-300e_in1k_20220927-1e4f3304.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/mocov3_resnet50_8xb512-amp-coslr-300e_in1k_20220915_180538.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-d21ddac2.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220920_113403.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ResNet50</td>
<td>800</td>
<td>4096</td>
<td>74.4</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/mocov3_resnet50_8xb512-amp-coslr-800e_in1k_20220927-e043f51a.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/mocov3_resnet50_8xb512-amp-coslr-800e_in1k_20220919_111209.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/resnet50_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-0e97a483.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220926_102021.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ViT-small</td>
<td>300</td>
<td>4096</td>
<td>73.6</td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k-224_20220826-08bc52f7.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k-224_20220721_153833.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-small-p16_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k_20220826-376674ef.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k_20220724_140850.json'>log</a></td>
<td>/</td>
</tr>
<tr>
<td>ViT-base</td>
<td>300</td>
<td>4096</td>
<td>76.9</td>
<td>83.0</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k-224_20220826-25213343.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k-224_20220725_104223.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb128-coslr-90e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k_20220826-83be7758.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k_20220729_004628.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb64-coslr-150e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k_20220826-f1e6c442.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k_20220809_103500.json'>log</a></td>
</tr>
<tr>
<td>ViT-large</td>
<td>300</td>
<td>4096</td>
<td>/</td>
<td>83.7</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k-224_20220829-9b88a442.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k-224_20220818_143032.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb64-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k_20220829-878a2f7f.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k_20220825_201433.json'>log</a></td>
</tr>
<tr>
<td rowspan="9">MAE</td>
<td>ViT-base</td>
<td>300</td>
<td>4096</td>
<td>60.8</td>
<td>83.1</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220829-c2cf66ba.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220718_152424.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220720_104514.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220713_140138.json'>log</a></td>
</tr>
<tr>
<td>ViT-base</td>
<td>400</td>
<td>4096</td>
<td>62.5</td>
<td>83.3</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-400e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k_20220825-bc79e40b.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k_20220628_200815.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220713_142534.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220708_183134.json'>log</a></td>
</tr>
<tr>
<td>ViT-base</td>
<td>800</td>
<td>4096</td>
<td>65.1</td>
<td>83.3</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-base-p16_8xb512-coslr-800e-fp16_in1k_20220825-5d81fbc4.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-base-p16_8xb512-coslr-800e-fp16_in1k_20220718_134405.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k20220721_203941.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220724_232940.json'>log</a></td>
</tr>
<tr>
<td>ViT-base</td>
<td>1600</td>
<td>4096</td>
<td>67.1</td>
<td>83.5</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k_20220825-f7569ca2.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k_20220815_103458.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220724_232557.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220825-cf70aa21.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220721_202304.json'>log</a></td>
</tr>
<tr>
<td>ViT-large</td>
<td>400</td>
<td>4096</td>
<td>70.7</td>
<td>85.2</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-large-p16_8xb512-amp-coslr-400e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k_20220825-b11d0425.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k_20220726_202204.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k_20220803_101331.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-400e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k_20220729_122511.json'>log</a></td>
</tr>
<tr>
<td>ViT-large</td>
<td>800</td>
<td>4096</td>
<td>73.7</td>
<td>85.4</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-large-p16_8xb512-amp-coslr-800e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k_20220825-df72726a.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k_20220804_104018.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k_20220808_092730.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-800e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k_20220730_235819.json'>log</a></td>
</tr>
<tr>
<td>ViT-large</td>
<td>1600</td>
<td>4096</td>
<td>75.5</td>
<td>85.7</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-large-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k_20220825-cc7e98c9.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k_20220806_210725.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k/vit-large-p16_linear-8xb2048-coslr-90e_in1k_20220813_155615.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-large-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-large-p16_8xb512-fp16-coslr-1600e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k/vit-large-p16_ft-8xb128-coslr-50e_in1k_20220813_125305.json'>log</a></td>
</tr>
<tr>
<td>ViT-huge-FT-224</td>
<td>1600</td>
<td>4096</td>
<td>/</td>
<td>86.9</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-huge-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220916-ff848775.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220814_135241.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-huge-p16_ft-8xb128-coslr-50e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k_20220916-0bfc9bfd.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k/vit-huge-p16_ft-8xb128-coslr-50e_in1k_20220829_114027.json'>log</a></td>
</tr>
<tr>
<td>ViT-huge-FT-448</td>
<td>1600</td>
<td>4096</td>
<td>/</td>
<td>87.3</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-huge-p16_8xb512-amp-coslr-1600e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220916-ff848775.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k_20220814_135241.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448_20220916-95b6a0ce.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-huge-p16_8xb512-fp16-coslr-1600e_in1k/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448/vit-huge-p16_ft-32xb8-coslr-50e_in1k-448_20220913_113737.json'>log</a></td>
</tr>
<tr>
<td>CAE</td>
<td>ViT-base</td>
<td>300</td>
<td>2048</td>
<td>/</td>
<td>83.3</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/cae/cae_vit-base-p16_16xb128-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k_20220825-404a1929.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k_20220615_163141.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k_20220825-f3d234cd.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k/vit-base-p16_ft-8xb128-coslr-100e-rpe_in1k_20220711_165500.json'>log</a></td>
</tr>
<tr>
<td rowspan="4">SimMIM</td>
<td>Swin-base-FT192</td>
<td>100</td>
<td>2048</td>
<td>/</td>
<td>82.7</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-100e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220829-0e15782d.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220827_034052.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k/swin-base_ft-8xb256-coslr-100e_in1k_20220829-9cf23aa1.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k/swin-base_ft-8xb256-coslr-100e_in1k_20220829_001452.json'>log</a></td>
</tr>
<tr>
<td>Swin-base-FT224</td>
<td>100</td>
<td>2048</td>
<td>/</td>
<td>83.5</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-100e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220829-0e15782d.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220827_034052.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k-224.py'>config</a> | model | log</td>
</tr>
<tr>
<td>Swin-base-FT224</td>
<td>800</td>
<td>2048</td>
<td>/</td>
<td>83.7</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192_20220916-a0e931ac.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192_20220906_141645.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k-224.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k-224/swin-base_ft-8xb256-coslr-100e_in1k-224_20221208-155cc6e6.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k-224/swin-base_ft-8xb256-coslr-100e_in1k-224_20221207_135847.json'>log</a></td>
</tr>
<tr>
<td>Swin-large-FT224</td>
<td>800</td>
<td>2048</td>
<td>/</td>
<td>84.8</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192_20220916-4ad216d3.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192_20220907_203738.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224_20220916-d4865790.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224_20220914_133331.json'>log</a></td>
</tr>
<tr>
<td>MaskFeat</td>
<td>ViT-base</td>
<td>300</td>
<td>2048</td>
<td>/</td>
<td>83.4</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221101-6dfc8bf3.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221019_194256.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb256-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k_20221028-5134431c.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/maskfeat/maskfeat_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k/vit-base-p16_ft-8xb256-coslr-100e_in1k_20221026_105344.json'>log</a></td>
</tr>
<tr>
<td>BEiT</td>
<td>ViT-base</td>
<td>300</td>
<td>2048</td>
<td>/</td>
<td>83.1</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221128-ab79e626.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221123_103802.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/beit/classification/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221128-0ca393e9.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221127_162126.json'>log</a></td>
</tr>
<tr>
<td>MILAN</td>
<td>ViT-base</td>
<td>400</td>
<td>4096</td>
<td>78.9</td>
<td>85.3</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k_20221129-180922e8.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k_20221123_112721.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/milan/classification/vit-base-p16_linear-8xb2048-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k-milan_20221129-74ac94fa.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k-milan_20221125_031826.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/milan/classification/vit-base-p16_linear-8xb2048-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k_20221129-03f26f85.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k_20221124_215401.json'>log</a></td>
</tr>
<tr>
<td>BEiT v2</td>
<td>ViT-base</td>
<td>300</td>
<td>2048</td>
<td>/</td>
<td>85.0</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221212-a157be30.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221206_012130.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/beitv2/classification/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221212-d1c0789e.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221211_155017.json'>log</a></td>
</tr>
<tr>
<td>EVA</td>
<td>ViT-base</td>
<td>400</td>
<td>4096</td>
<td>69.0</td>
<td>83.7</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k_20221226-26d90f07.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k_20221220_113809.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/elfsup/eva/classification/vit-base-p16_linear-8xb2048-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k_20221226-ef51bf09.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k_20221222_134137.json'>log</a></td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/eva/classification/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221226-f61cf992.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/eva/eva-mae-style_vit-base-p16_16xb256-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221221_212618.json'>log</a></td>
</tr>
<tr>
<td>MixMIM</td>
<td>MixMIM-Base</td>
<td>400</td>
<td>2048</td>
<td>/</td>
<td>84.6</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mixmim/mixmim-base-p16_16xb128-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mixmim/mixmim-base-p16_16xb128-coslr-300e_in1k/mixmim-base-p16_16xb128-coslr-300e_in1k_20221208-44fe8d2c.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mixmim/mixmim-base-p16_16xb128-coslr-300e_in1k/mixmim-base-p16_16xb128-coslr-300e_in1k_20221204_134711.json'>log</a></td>
<td>/</td>
<td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mixmim/classification/mixmim-base-p16_ft-8xb128-coslr-100e-in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mixmim/mixmim-base-p16_16xb128-coslr-300e_in1k/mixmim-base-p16_ft-8xb128-coslr-100e_in1k/mixmim-base-p16_ft-8xb128-coslr-100e_in1k_20221208-41ecada9.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mixmim/mixmim-base-p16_16xb128-coslr-300e_in1k/mixmim-base-p16_ft-8xb128-coslr-100e_in1k/mixmim-base-p16_ft-8xb128-coslr-100e_in1k_20221206_143046.json'>log</a></td>
</tr>
</tbody>
</table>