Metadata-Version: 2.1
Name: self_supervised
Version: 0.0.1.6
Summary: Self Supervised Learning Algorithms Extension to Fastai
Home-page: https://github.com/keremturgutlu/self_supervised/tree/master/
Author: Kerem Turgutlu
Author-email: keremturgutlu@gmail.com
License: Apache Software License 2.0
Description: # Self Supervised Learning Fastai Extension
        > Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks.
        
        
        You may find documentation [here](https://keremturgutlu.github.io/self_supervised)
        
        ## Install
        
        `pip install <>`
        
        ## Algorithms
        
        Here are the list of implemented algorithms:
        
        - [SimCLR](https://arxiv.org/pdf/2002.05709.pdf)
        - [BYOL](https://arxiv.org/pdf/2006.07733.pdf)
        - [SwAV](https://arxiv.org/pdf/2006.09882.pdf)
        
        ## ImageWang Benchmarks
        
        All of the algorithms implemented in this library have been evaluated in [ImageWang Leaderboard](https://github.com/fastai/imagenette#image%E7%BD%91-leaderboard). 
        
        In overall superiority of the algorithms are as follows `SwAV > BYOL > SimCLR` in most of the benchmarks. For details you may inspect the history of [ImageWang Leaderboard](https://github.com/fastai/imagenette#image%E7%BD%91-leaderboard) through github. 
        
        It should be noted that during these experiments no hyperparameter selection/tuning was made beyond using `learn.lr_find()` or making sanity checks over data augmentations by visualizing batches. So, there is still space for improvement and overall rankings of the alogrithms may change based on your setup. Yet, the overall rankings are on par with the papers.
        
        ## Contributing
        
        Contributions and or requests for new self-supervised algorithms are welcome. This repo will try to keep itself up-to-date with recent SOTA self-supervised algorithms.
        
        Before raising a PR please create a new branch with name `<self-supervised-algorithm>`. You may refer to previous notebooks before implementing your Callback.
        
        Please refer to sections `Developers Guide, Abbreviations Guide, and Style Guide` from https://docs.fast.ai/dev-setup and note that same rules apply for this library.
        
Keywords: self supervised learning,feature learning,deep learning,fastai
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
