[HN Gopher] Lessons learned from manually classifying CIFAR-10 (...
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       Lessons learned from manually classifying CIFAR-10 (2011)
        
       Author : djoldman
       Score  : 54 points
       Date   : 2024-04-09 10:48 UTC (1 days ago)
        
 (HTM) web link (karpathy.github.io)
 (TXT) w3m dump (karpathy.github.io)
        
       | 01HNNWZ0MV43FF wrote:
       | > The state of the art is currently at about 80% classification
       | accuracy
       | 
       | 13 years later, I guess it's around 99% accuracy.
       | 
       | https://en.wikipedia.org/wiki/CIFAR-10#Research_papers_claim...
        
       | karpathy wrote:
       | Hah why is this on HN today?
       | 
       | Update from 2024:
       | 
       | https://github.com/tysam-code/hlb-CIFAR10 Train to 94% on
       | CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110
       | seconds (or less!)
       | 
       | https://paperswithcode.com/sota/image-classification-on-cifa...
       | 99.5% SOTA
       | 
       | so that's embarrassing :)
        
         | djoldman wrote:
         | I posted it because it was linked to by Keller Jordan:
         | 
         | https://arxiv.org/abs/2404.00498v2
        
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       (page generated 2024-04-10 23:01 UTC)