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+ # eval2_90
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+ SmolVLA policy for Eval 2.
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+ Dataset:
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+ - `robot-learning-group47/eval2_90_chengming_promptaug_v1`
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+ Training setup:
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+ - Base policy: `lerobot/smolvla_base`
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+ - One real camera: `observation.images.front`
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+ - Camera mapping: `observation.images.front` → `observation.images.camera1`
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+ - `empty_cameras=2`
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+ - Dynamic prompt sampling: random prompt sampled within the same layout-target bucket during training
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+ - `n_obs_steps=1`
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+ - `chunk_size=50`
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+ - `n_action_steps=50`
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+ - Batch size: 64
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+ - Steps: 30,000
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+ - Save frequency: 2,500
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+ - `train_expert_only=true`
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+ - `freeze_vision_encoder=true`
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+ - `num_vlm_layers=16`
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+ - Learning rate: `1e-4`
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+ - Weight decay: `1e-10`
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+ The repo root contains the latest checkpoint for direct loading.
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+ All intermediate checkpoints are stored under:
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+ `checkpoints/`