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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