---
license: mit
tags:
  - lerobot
  - act
  - libero
  - robot-learning
---

# act-libero-baseline-2026-03-29-005757-1k

備份自 ID Lab lerobot-vla-fbagent 專案，含完整中間 checkpoint。

## 訓練資訊

| 項目 | 值 |
|------|-----|
| Policy Type | `act` |
| Dataset | `HuggingFaceVLA/libero` |
| Max Steps | 1,000 |
| Checkpoints | 1 個 |
| Seed | ? |
| Batch Size | ? |
| Learning Rate | ? |
| Num Workers | ? |
| Chunk Size | 100 |
| Git Commit | `d440da2` |
| Source Dir | `00-57-57_act` |

## 復現指令

```bash
git clone --recurse-submodules git@github.com:KunHsiang/lerobot-vla-fbagent.git
cd lerobot-vla-fbagent
git checkout d440da2
uv sync

HF_HUB_ENABLE_HF_TRANSFER=1 .venv/bin/python scripts/train_with_fb.py \
    --policy.type=act \
    --policy.repo_id=kunhsiang/act-libero-baseline-2026-03-29-005757-1k \
    --dataset.repo_id=HuggingFaceVLA/libero \
    --training.seed=? \
    --training.batch_size=? \
    --training.learning_rate=? \
    --training.num_workers=?
```

## Checkpoint 結構

```
checkpoints/
  001000/          # step 1,000
  ...
  001000/          # final (1,000 steps)
```

每個 step 目錄包含:
- `pretrained_model/model.safetensors` — 模型權重
- `pretrained_model/config.json` — 模型設定
- `pretrained_model/train_config.json` — 完整訓練設定
- `training_state/optimizer_state.safetensors` — Optimizer 狀態（可 resume）
- `training_state/rng_state.safetensors` — RNG 狀態（可 resume）

## Resume 訓練

```bash
.venv/bin/python scripts/train_with_fb.py \
    --policy.type=act \
    --resume=true \
    --policy.pretrained_path=checkpoints/001000/pretrained_model
```