作者您好,请问如何使用训练好的Checkpoint评估模型
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Problem
您好,我使用PTPCG模型跑了100个epoch,保存了最佳的Checkpoint。现在我想使用这个Checkpoint评估我重新划分后的ChFinAnn数据集(按照论元数量重新划分了一下),应该怎么做呢?
You can reproduce the problem by ...
I have tried ..., but it goes to ...
I have checked the source codes, and the problem may come from ...
Environment
| Environment | Values |
|---|---|
| System | Windows/Linux |
| GPU Device | |
| CUDA Version | |
| Python Version | |
| PyTorch Version | |
| dee (the Toolkit) Version |
Full Log
Log:
嗨,感谢您对我们项目的关注~
可以参考这里的代码,使用和训练相似的设置,增加模型导入,跳过训练过程,直接评价:https://github.com/Spico197/DocEE/blob/main/run_dee_task.py#L273-L284
你好。我直接将skip_train超参数改为True,然后更换了划分后的新数据集,但是最终评估的结果还是之前训练时保存的评估结果。
请问是还需要修改什么地方吗?
你好。我直接将skip_train超参数改为True,然后更换了划分后的新数据集,但是最终评估的结果还是之前训练时保存的评估结果。
了解了,看起来像是直接输出了之前的结果,没有重新在新数据上推理。重新调用一下dee_task.eval试试看。
https://github.com/Spico197/DocEE/blob/main/dee%2Ftasks%2Fdee_task.py#L854-L861
好的,我尝试一下,感谢回复
