OpenMotionLab / MotionGPT

[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs
https://motion-gpt.github.io
MIT License
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Difference Between Testing Results and Paper Results #97

Open Iris1946 opened 4 months ago

Iris1946 commented 4 months ago

Hello, I encountered a significant difference when reproducing the results for the t2m task, which is similarly reported in Issue 49.

Below is a comparison of the results:

R_top1 R_top2 R_top3 FID MMDist Diversity MModality
ground truth 0.511 0.702 0.798 0.002 2.967 9.422 -
paper result 0.492 0.681 0.778 0.232 3.096 9.528 2.008
my result (last.ckpt) 0.322 0.467 0.554 0.491 4.738 9.231 4.673
my result (mgpt.tar) 0.402 0.568 0.659 0.185 4.019 9.294 3.501

First, I tried to train my own MotionGPT models and set the parameters in config_h3d_stage3.yaml as follows:

TRAIN:
  PRETRAINED: 'experiments/mgpt/Pretrain_HumanML3D/checkpoints/last.ckpt' # Pretrained model path
  PRETRAINED_VAE: experiments/mgpt/VQVAE_HumanML3D/checkpoints/last.ckpt # Vae model path

TEST:
  CHECKPOINTS: experiments/mgpt/Instruct_HumanML3D/checkpoints/last.ckpt

The results differed significantly from those reported in the paper. Therefore, I attempted to use the checkpoint downloaded from Hugging Face and set the parameters in config_h3d_stage3.yaml as follows:

TRAIN:
  PRETRAINED: 'checkpoints/MotionGPT-base/motiongpt_s3_h3d.tar' # Pretrained model path
  PRETRAINED_VAE: experiments/mgpt/VQVAE_HumanML3D/checkpoints/last.ckpt # Vae model path

TEST:
  CHECKPOINTS: checkpoints/MotionGPT-base/motiongpt_s3_h3d.tar

However, I was still unable to reproduce the results from the paperšŸ˜­

The attachments are the testing logs: mgpt_tar.log , last_ckpt.log.

Thank you very much for your assistancešŸ˜Š

www-Ye commented 2 months ago

Hello, I got similar results when I reproduced it. The checkpoint of R_top1 index is only about 0.4, and the model obtained by retraining based on T5 is only a little over 0.3. Have you found a solution?