a3124371940/radeonvla_reflex_smolvla_2k_200k

RadeonVLA-Reflex SmolVLA Physical-2K cumulative-200K Model Card

Release status: cumulative-200K checkpoint complete, locally hash-verified, and evaluated on 100 disjoint-seed strict-physics rollouts. The learned first attempt succeeds on 36/100; the explicitly enabled Precision-Reflex system finishes 91/100.

Model

• Base model: lerobot/smolvla_base
• Base revision: c83c3163b8ca9b7e67c509fffd9121e66cb96205
• Fine-tuned checkpoint: Physical-1K 100K history + Physical-2K 100K continuation
• Public URL: https://huggingface.co/a3124371940/radeonvla_reflex_smolvla_2k_200k
• Local checkpoint tree SHA256: ad0ec7c1271b73b0ba684180b71a80ae1a9dad22c64a38796ba28f6597991683
• Evaluation implementation: c5c37576d4b80f056205ef7920a5f1ebfa614f86
• Dataset: https://huggingface.co/datasets/a3124371940/radeonvla_reflex_physical_2k
• Dataset revision: 2779b7c5566df9072bb9a7c43335d6203ea97887

Intended use

Language-conditioned Franka fruit sorting in the project Genesis scene.

Inputs and outputs

• Image inputs: observation.images.world + observation.images.wrist (320×240 RGB); renamed to camera1/camera2 for SmolVLA
• State shape and ordering: 9-D qpos — panda_joint1..7, panda_finger_joint1..2
• Language input: natural-language task instruction
• Action type, shape, and ordering: 9-D absolute joint positions (same order as state)
• Control frequency: 20 Hz
• Action chunk size: determined by SmolVLA checkpoint config

Training

Item	Value
Radeon GPU	AMD Radeon Graphics, gfx1100, 51.5 GB VRAM
ROCm	7.2.1 / HIP runtime 7.2.53211
PyTorch	2.9.1+rocm7.2.1
Precision	FP32 (use_amp=false)
Batch size	4
Gradient accumulation	Not configured; one optimizer update per batch
Cumulative training steps	approximately 200,000
Final continuation	100,000 steps / 400,000 sampled frames
Final continuation time	3h 45m 32s
Final throughput	30 samples/s / 7.41 optimizer steps/s
Peak training memory reported by LeRobot	2.22 GB
Final logged minibatch loss	0.058

Evaluation

The formal benchmark covers 20 L1 tasks × 5 disjoint seeds (100 total, seeds 52000–52099) using the exact language stored during collection. first_attempt_success measures learned SmolVLA execution. When explicitly enabled, Precision Reflex handles terminal failures with the strict-physics geometry controller under forbid_rigid_pose_writes() and allow_kinematic_assist=False; no fruit pose reset, teleport, grasp glue, or placement nudge is permitted.

Metric	Result
Learned first-attempt success	36/100 (36.0%; Wilson 95% CI 27.3–45.8%)
Precision-recovery attempts	63
Precision-recovery success	55/63 (87.3%)
Precision-recovery contribution	55/100 (55.0 points)
Final system success	91/100 (91.0%; Wilson 95% CI 83.8–95.2%)
Inference latency P50 / P95	4.54 ms / 37.27 ms

The nine retained failures are eight empty_grasp events and one wrong_object event. Final success by fruit is apple 20/20, banana 19/20, lemon 19/20, orange 17/20, and plum 16/20. The latency values were recorded while five disjoint evaluation partitions shared one Radeon GPU and therefore include concurrent-evaluation contention.

Limitations

Training and evaluation are limited to Genesis simulation. Coverage includes the registered language and task suite, dual RGB cameras at 320×240, and 9-D absolute joint actions. Precision recovery uses simulator geometry and is not evidence of learned visual recovery. Real-robot transfer is outside the current evaluation scope. The published card lists failure modes observed in the final evaluation run.

License note

The upstream lerobot/smolvla_base repository did not declare license metadata when the base revision above was frozen. This model card therefore uses Hugging Face's other marker instead of inventing a permissive license. The Physical-2K training dataset is CC BY 4.0 and its attribution requirements remain applicable to the dataset and rendered examples. Users must review the upstream base-model terms before redistribution or commercial use.