Skip to content

Same data but has large different while evaluating in the training stage vs evaluate it standalone from read the finetuned-model #37265

@irmathebest

Description

@irmathebest

Hi team.
I have stuck on this problem for a whole week and still cannot figure out why.
Env: python 3.8, transformer -- 4.28
I am using the XLMRobertA Base for finetuning the model for a multi-class classification.
However,
when in the training step, I run trainer.evaluate() it shows the accuracy is 68% while in the evaluate standalone, which it reads the base model and then make the prediction and evaluate it, the accuracy drops to 30%. Is there any reason why it happens, or it's a bug?

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions