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pravsels/
dit_coffee_norm_fix

Name: dit_coffee_norm_fix
Availability: InStock

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dit_coffee_norm_fix

Diffusion policy checkpoint for the bin_pick_pack_coffee_capsules task, trained with per-timestep (H,D) RAMEN action normalization and corrected action chunk semantics (slot 0 = current action).

Checkpoint

Step	train_loss	Status	Hash
29000	0.0021	partial (29k/50k)	`29a146d1768da5d94e0d6b9582c7bc890fa55efc050512e4131171d699499fec`

Training was interrupted by walltime (1 day limit) at step ~29062/50000. Loss was still decreasing healthily — this checkpoint will be resumed.

Config

dataset: villekuosmanen/bin_pick_pack_coffee_capsules
batch_size: 80 per GPU (320 global, 4x GPUs)
optimizer_lr: 3e-4
lr_scheduler: cosine (warmup 500 steps, min_lr_scale 0.1)
horizon: 32, n_action_steps: 32
noise_scheduler: DDIM, 100 train timesteps, 20 inference steps
observation_encoder: CLIP ViT-B/16 (vision + text)
action normalization: RAMEN with per-timestep stats (H=32, D=17)

Files

checkpoints/29000/params/model.safetensors   # model weights
checkpoints/29000/params/config.json         # model config
assets/ramen_stats.json                      # action normalization stats
TRAINING_LOG.md                              # sanitized training log

Verify integrity

bash

cd checkpoints/29000/params
find config.json model.safetensors -type f | sort | xargs sha256sum | sha256sum
# expected: 29a146d1768da5d94e0d6b9582c7bc890fa55efc050512e4131171d699499fec

Note: ramen_stats.json is in assets/, not in the params directory. The hash above covers only the params files. To reproduce the full hash including ramen_stats, download all three files into one directory and run the same command over all three.

W&B

Training dashboard

Source

repo: pravsels/multitask_dit_policy (branch stage1-multimodal-abstraction)

pravsels/dit_coffee_norm_fix