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Implemention of the Decision-Pretrained Transformer (DPT) from the paper Supervised Pretraining Can Learn In-Context Reinforcement Learning.

Python 98.24% Shell 1.76%

decision-pretrained-transformer's Issues

Doubts about some darkroom environment reproductions

Hello, recently I saw this paper of DPT, it is a very interesting work, I am very interested in it and try to reproduce it on your open source code. when I was reproducing the DPT Darkroom environment, I run run_darkroom.sh to training 1000 epochs. But the result is not quite consistent with Figure 7 of the paper, I don't know which detail is the problem, I hope to get your reply answer, thank you.
The following is the result of my reproduction and the results of the paper：
darkroom_heldout_shufTrue_lr0 001_do0_embd32_layer4_head4_envs100000_hists1_samples1_H100_d10_seed1_hor100 pkl_bar

企业微信截图_17138443781790

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