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Release status: trained checkpoint. The Physical-1K data and checkpoint are published; formal closed-loop evaluation of this checkpoint is still in progress and no final success rate is claimed in this revision.
c83c3163b8ca9b7e67c509fffd9121e66cb96205020000/pretrained_model47911b0faf672905107dd7daf18b5a99eaf199a01dcc579f62253fc4a3016308be62f684c7e916e8600cf37b8644883f8b75a7ddb0f72c60e9100739fd82bd498c8f3d9bed7b75af| 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 |
| Training steps | 20,000 (80,000 sampled frames) |
| Training time | 45m 34s |
| Peak training memory reported by LeRobot | 2.22 GB |
| Final logged minibatch loss | 0.091 |
SmolVLAPolicy.from_pretrained load test after
vendoring its VLM tokenizer and processor assets. A later revision will bind the formal
evaluation JSON, Normal-vs-Reflex comparison, inference latency, and observed failure
modes without replacing the immutable training metadata above.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-1K 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.