Hi, Thank you for this great work
While trying to run flow-matching waypoint inference against the released checkpoints (Qwen2.5-VL-SAFE-GRPO and Qwen2-VL-SAFE-GRPO via ModelScope, following the train_branch="fm" path from utils/citywalker.py), the predicted waypoints don't appear to be sensible on real test image sequences, not resembling plausible navigation trajectories.
The checkpoint files themselves might suggest why, as both published checkpoints look like unfinished, mid-training GRPO snapshots.
-
trainer_state.json shows training appears to be stopped early in both cases:
- Qwen2.5-VL-SAFE-GRPO: global_step=8000 / max_steps=125000 (6.4%), epoch=0.32/5
- Qwen2-VL-SAFE-GRPO: global_step=17600 / max_steps=301420 (5.8%), epoch=0.58/10
-
Both ship full distributed-training resumption state (optimizer.pt, scheduler.pt, training_args.bin, per-rank rng_state_N.pth
files)
-
best_global_step/best_metric/best_model_checkpoint are all null in both trainer_state.json files.
-
The HF contain only the auto-generated .gitattributes file.
Question: are the ModelScope uploads intended to be the final checkpoints, or were the fully-trained weights not yet pushed? If
these are final, are there any known issues with the flow-matching action head at inference time that would explain nonsensical
waypoint output?
Thank you so much for your help.
Hi, Thank you for this great work
While trying to run flow-matching waypoint inference against the released checkpoints (Qwen2.5-VL-SAFE-GRPO and Qwen2-VL-SAFE-GRPO via ModelScope, following the train_branch="fm" path from utils/citywalker.py), the predicted waypoints don't appear to be sensible on real test image sequences, not resembling plausible navigation trajectories.
The checkpoint files themselves might suggest why, as both published checkpoints look like unfinished, mid-training GRPO snapshots.
trainer_state.json shows training appears to be stopped early in both cases:
Both ship full distributed-training resumption state (optimizer.pt, scheduler.pt, training_args.bin, per-rank rng_state_N.pth
files)
best_global_step/best_metric/best_model_checkpoint are all null in both trainer_state.json files.
The HF contain only the auto-generated .gitattributes file.
Question: are the ModelScope uploads intended to be the final checkpoints, or were the fully-trained weights not yet pushed? If
these are final, are there any known issues with the flow-matching action head at inference time that would explain nonsensical
waypoint output?
Thank you so much for your help.