docs: Grokfast

Author: kozistr

README.md

@@ -10,7 +10,7 @@
 
 **pytorch-optimizer** is optimizer & lr scheduler collections in PyTorch. 
 I just re-implemented (speed & memory tweaks, plug-ins) the algorithm while based on the original paper. Also, It includes useful and practical optimization ideas.  
-Currently, **68 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!  
+Currently, **69 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!  
 
 Highly inspired by [pytorch-optimizer](https://github.com/jettify/pytorch-optimizer).
 
@@ -165,6 +165,7 @@ supported_optimizers = get_supported_optimizers()
 | bSAM          | *SAM as an Optimal Relaxation of Bayes*                                                           | [github](https://github.com/team-approx-bayes/bayesian-sam)                                                    | <https://arxiv.org/abs/2210.01620>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2022arXiv221001620M/exportcitation)                                      |
 | Schedule-Free | *Schedule-Free Optimizers*                                                                        | [github](https://github.com/facebookresearch/schedule_free)                                                    | <https://github.com/facebookresearch/schedule_free>                                        | [cite](https://github.com/facebookresearch/schedule_free)                                                         |
 | FAdam         | *Adam is a natural gradient optimizer using diagonal empirical Fisher information*                | [github](https://github.com/lessw2020/fadam_pytorch)                                                           | <https://arxiv.org/abs/2405.12807>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240512807H/exportcitation)                                      |
+| Grokfast      | *Accelerated Grokking by Amplifying Slow Gradients*                                               | [github](https://github.com/ironjr/grokfast)                                                                   | <https://arxiv.org/abs/2405.20233>                                                         | [cite](https://github.com/ironjr/grokfast?tab=readme-ov-file#citation)                                            |
 
 ## Supported LR Scheduler
 
@@ -325,7 +326,7 @@ If you use this software, please cite it below. Or you can get it from "cite thi
         month = jan,
         title = {{pytorch_optimizer: optimizer & lr scheduler & loss function collections in PyTorch}},
         url = {https://github.com/kozistr/pytorch_optimizer},
-        version = {2.12.0},
+        version = {3.0.1},
         year = {2021}
     }
 

docs/index.md

@@ -10,7 +10,7 @@
 
 **pytorch-optimizer** is optimizer & lr scheduler collections in PyTorch. 
 I just re-implemented (speed & memory tweaks, plug-ins) the algorithm while based on the original paper. Also, It includes useful and practical optimization ideas.  
-Currently, **68 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!  
+Currently, **69 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!  
 
 Highly inspired by [pytorch-optimizer](https://github.com/jettify/pytorch-optimizer).
 
@@ -165,6 +165,7 @@ supported_optimizers = get_supported_optimizers()
 | bSAM          | *SAM as an Optimal Relaxation of Bayes*                                                           | [github](https://github.com/team-approx-bayes/bayesian-sam)                                                    | <https://arxiv.org/abs/2210.01620>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2022arXiv221001620M/exportcitation)                                      |
 | Schedule-Free | *Schedule-Free Optimizers*                                                                        | [github](https://github.com/facebookresearch/schedule_free)                                                    | <https://github.com/facebookresearch/schedule_free>                                        | [cite](https://github.com/facebookresearch/schedule_free)                                                         |
 | FAdam         | *Adam is a natural gradient optimizer using diagonal empirical Fisher information*                | [github](https://github.com/lessw2020/fadam_pytorch)                                                           | <https://arxiv.org/abs/2405.12807>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240512807H/exportcitation)                                      |
+| Grokfast      | *Accelerated Grokking by Amplifying Slow Gradients*                                               | [github](https://github.com/ironjr/grokfast)                                                                   | <https://arxiv.org/abs/2405.20233>                                                         | [cite](https://github.com/ironjr/grokfast?tab=readme-ov-file#citation)                                            |
 
 ## Supported LR Scheduler
 
@@ -325,7 +326,7 @@ If you use this software, please cite it below. Or you can get it from "cite thi
         month = jan,
         title = {{pytorch_optimizer: optimizer & lr scheduler & loss function collections in PyTorch}},
         url = {https://github.com/kozistr/pytorch_optimizer},
-        version = {2.12.0},
+        version = {3.0.1},
         year = {2021}
     }