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hackhackhack66666/OAT-BLT-Libero-700
OAT-BLT-Libero-700 is a robotics model from hackhackhack66666. Use it for the robotics task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Hugging Face model repository for a dense cross-attention OAT policy trained on LIBERO-10 (N500). This snapshot was taken at epoch 700 during a long run (oatdensewithuidlong0530220204).
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Updated Jun 1, 2026
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From the Hugging Face model README
Hugging Face model repository for a dense cross-attention OAT policy trained on
LIBERO-10 (N500). This snapshot was taken at epoch 700 during a long run
(oat_dense_with_uid_long_0530_220204).
| File | Description |
|---|---|
ep-0700.ckpt | PyTorch workspace checkpoint (~729 MB) |
training_logs.jsonl | Full training JSONL (train/val curves) |
training_metrics_dashboard.png | Training loss dashboard |
overfit_watcher/ | Counterfactual early-stop reports |
sim_eval/ | Phase A screen eval (30 ep/task) |
sim_eval_phase_b/ | Phase B confirm eval (50 ep/task, 3 exp) — ep-0700 only |
experiment_log_dense_visual_memory.md | Experiment journal |
| Train loss | Val loss | Reconst MSE | Sim SR (Phase A) |
|---|---|---|---|
| 2.067359447479248 | 5.751441478729248 | 0.07376550883054733 | 51.7% |

Mean success rate: 51.7% — 30 episodes/task, 300 total rollouts, seed 1000.
Details: sim_eval/eval_summary.md · sim_eval/eval_log.json

Mean success rate: 47.60% ± 1.75% — official-style protocol for comparison with OAT paper (~56.3%).

Details: sim_eval_phase_b/ (separate from Phase A sim_eval/ — not overwritten).
use_dense_visual_memory=true (spatial visual tokens + cross-attn)use_state_memory_tokens=true)libero10_N500.zarrPaper OAT8 on LIBERO-10: ~56.3% mean success rate (external reference).
If you use this checkpoint, please cite OAT: Ordered Action Tokenization and specify epoch 700 of the dense LIBERO-10 ladder.