The following pi0-fast weights were obtained by training on 4 A100 GPUs for 10k iterations using five tasks (2500 episodes) from the primitive-ft-dataset, shared for community reference.

The five primitive tasks used to train are: [select_fruit, select_toy, select_painting, select_poker, select_mahjong]. These tasks involve similar skills and simple actions, making them suitable for research on downstream adaptation and generalization abilities.

The training codes are available at: https://github.com/Shiduo-zh/openpi. If any issues or bugs are encountered during training, feel free to contact our team.

Track select_toy_SR select_toy_PS select_fruit_SR select_fruit_PS select_painting_SR select_painting_PS select_poker_SR select_poker_PS select_mahjong_SR select_mahjong_PS Avg_SR
track_1_in_distribution 0.34 0.6 0.44 0.67 0.24 0.24 0.22 0.387 0.25 0.417 0.298
track_2_cross_category 0.16 0.45 0.48 0.67 0.12 0.12 0.14 0.227 0.143 0.204 0.209
track_3_common_sense 0.28 0.54 0.24 0.4 0.18 0.18 0.04 0.193 0.064 0.064 0.161
track_4_semantic_instruction 0.22 0.5 0.294 0.471 0.08 0.08 0.08 0.207 0.146 0.208 0.164
track_6_unseen_texture 0.28 0.55 0.52 0.7 0.24 0.24 0.26 0.367 0.319 0.436 0.324
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