The question of pre-training accuracy about pointmamba HOT 7 CLOSED

May I ask if you can directly test with the weights you provide? The accuracy of the test in pointmamba is only 7%~8%, and the weight files provided by them are also used in point-MAE, with about 93.5%

I just re-cloned the repository, downloaded the open-sourced checkpoint, and achieved the exact same results as reported. The test command should be CUDA_VISIBLE_DEVICES=0 python main.py --test --config cfgs/finetune_modelnet.yaml --ckpts modelnet_scratch.pth.

from pointmamba.

并且当我训练的时候 会nan 同样的数据，在mae中可以正常训练 请问可以直接使用代码中的超参数吗，需要针对性调整？

I'm sorry, we never encountered an issue with NaN.

from pointmamba.

Thank you for your interest in our work!

The code currently open-sourced from the repository aligns with the paper's current version. Our models are all trained and tested using a single RTX 4090, which may differ across hardware platforms. Also please refer to this issue and the explanation here.

Feel free to evaluate our open-sourced weight for ModelNet40.

from pointmamba.

May I ask if you can directly test with the weights you provide? The accuracy of the test in pointmamba is only 7%~8%, and the weight files provided by them are also used in point-MAE, with about 93.5%

from pointmamba.

并且当我训练的时候

会nan
同样的数据，在mae中可以正常训练
请问可以直接使用代码中的超参数吗，需要针对性调整？

from pointmamba.

并且当我训练的时候 会nan 同样的数据，在mae中可以正常训练 请问可以直接使用代码中的超参数吗，需要针对性调整？

I'm sorry, we never encountered an issue with NaN.

Thank you very much for your answer~

from pointmamba.

I am closing this issue. Please feel free to reopen it if necessary.

from pointmamba.