Metadata-Version: 2.1
Name: LRBench
Version: 0.0.0.1
Summary: A learning rate recommending and benchmarking tool.
Home-page: https://github.com/git-disl/LRBench
Author: Yanzhao Wu
Author-email: yanzhaowumail@gmail.com
License: UNKNOWN
Download-URL: https://github.com/git-disl/LRBench/archive/master.zip
Description: <!--- Project Logo --->
        # LRBench
        <!--- a href=""><img src="" alt=""></a --->
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        [![GitHub license](https://img.shields.io/badge/license-apache-green.svg?style=flat)](https://www.apache.org/licenses/LICENSE-2.0)
        [![Version](https://img.shields.io/badge/version-0.0.1-red.svg?style=flat)]()
        <!---
        [![Travis Status]()]()
        [![Jenkins Status]()]()
        [![Coverage Status]()]()
        --->
        ## Introduction
        
        A learning rate benchmarking and recommending tool, which will help practitioners efficiently select and compose good learning rate policies.
        
        * Semi-automatic Learning Rate Tuning
        * Evaluation: A set of Useful Metrics, covering Utility, Cost, and Robustness.
        * Verification: Near-optimal Learning Rate
        
        If you find this tool useful, please cite the following paper:
        
            @ARTICLE{lrbench2019,
              author = {{Wu}, Yanzhao and {Liu}, Ling and {Bae}, Juhyun and {Chow}, Ka-Ho and
              {Iyengar}, Arun and {Pu}, Calton and {Wei}, Wenqi and {Yu}, Lei and
              {Zhang}, Qi},
              title = "{Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks}",
              journal = {arXiv e-prints},
              keywords = {Computer Science - Machine Learning, Statistics - Machine Learning},
              year = "2019",
              month = "Aug",
              eid = {arXiv:1908.06477},
              pages = {arXiv:1908.06477},
              archivePrefix = {arXiv},
              eprint = {1908.06477},
              primaryClass = {cs.LG},
              adsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv190806477W},
              adsnote = {Provided by the SAO/NASA Astrophysics Data System}
            }
        
        ## Problem
        
        
        ## Installation
        
        
        ## Supported Platforms
        
        
        ## Development / Contributing
        
        
        ## Issues
        
        
        ## Status
        
        
        ## Contributors
        
        See the [people page](https://github.com/git-disl/LRBench/graphs/contributors) for the full listing of contributors.
        
        ## License
        
        Copyright (c) 20XX-20XX [Georgia Tech DiSL](https://github.com/git-disl)  
        Licensed under the [Apache License](LICENSE).
        
Keywords: LEARNING RATE,TRAINING,DEEP LEARNING
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
