Skip to content

The problem of accuracy? #4

@Zhangwenyao1

Description

@Zhangwenyao1

Thanks for your great job!
When I run this code with COOP, I find the result of trained on oxford_flowers is great,
=> result
=> result

  • total: 2,463
  • correct: 2,332
  • accuracy: 94.7%
  • error: 5.3%
  • macro_f1: 94.6%
    Elapsed: 0:15:09
    But if I run it again(as your code show, it will use the model I trained last time, which got good results), it gets a bad result as follows:
    => result
  • total: 2,463
  • correct: 24
  • accuracy: 1.0%
  • error: 99.0%
  • macro_f1: 0.1%
    Elapsed: 0:00:11
    I am not sure why it produces a bad result, can you give me some advice.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions