Instructions to use arclabmit/xarm7_act_beavrsim_shellgame_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use arclabmit/xarm7_act_beavrsim_shellgame_model with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -2,12 +2,27 @@
|
|
| 2 |
datasets: arclabmit/xarm7_beavrsim_shellgame_dataset
|
| 3 |
library_name: lerobot
|
| 4 |
license: apache-2.0
|
| 5 |
-
model_name: act
|
| 6 |
pipeline_tag: robotics
|
| 7 |
tags:
|
| 8 |
- robotics
|
| 9 |
- lerobot
|
| 10 |
- act
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
---
|
| 12 |
|
| 13 |
# Model Card for act
|
|
@@ -59,4 +74,23 @@ Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a
|
|
| 59 |
|
| 60 |
## Model Details
|
| 61 |
|
| 62 |
-
- **License:** apache-2.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
datasets: arclabmit/xarm7_beavrsim_shellgame_dataset
|
| 3 |
library_name: lerobot
|
| 4 |
license: apache-2.0
|
|
|
|
| 5 |
pipeline_tag: robotics
|
| 6 |
tags:
|
| 7 |
- robotics
|
| 8 |
- lerobot
|
| 9 |
- act
|
| 10 |
+
model-index:
|
| 11 |
+
- name: xarm7_act_beavrsim_shellgame_model
|
| 12 |
+
results:
|
| 13 |
+
- task:
|
| 14 |
+
type: robotics
|
| 15 |
+
name: Robotic Manipulation
|
| 16 |
+
dataset:
|
| 17 |
+
name: beavr_sim
|
| 18 |
+
type: simulation
|
| 19 |
+
metrics:
|
| 20 |
+
- type: success_rate
|
| 21 |
+
value: 10.299999999999999
|
| 22 |
+
name: Success Rate
|
| 23 |
+
- type: reward
|
| 24 |
+
value: -0.05
|
| 25 |
+
name: Avg Reward
|
| 26 |
---
|
| 27 |
|
| 28 |
# Model Card for act
|
|
|
|
| 74 |
|
| 75 |
## Model Details
|
| 76 |
|
| 77 |
+
- **License:** apache-2.0
|
| 78 |
+
|
| 79 |
+
|
| 80 |
+
<!-- EVAL_RESULTS_START -->
|
| 81 |
+
## Evaluation Results
|
| 82 |
+
*Evaluated on 2026-02-05 09:45*
|
| 83 |
+
|
| 84 |
+
| Metric | Value |
|
| 85 |
+
| :--- | :--- |
|
| 86 |
+
| **Success Rate** | 10.3% |
|
| 87 |
+
| **Average Reward** | -0.050 |
|
| 88 |
+
| **Max Reward (Avg)** | 1.030 |
|
| 89 |
+
| **Episodes** | 1000 |
|
| 90 |
+
| **Eval Speed** | 2.47 s/ep |
|
| 91 |
+
| **Seed** | 26 |
|
| 92 |
+
|
| 93 |
+
> [!TIP]
|
| 94 |
+
> Detailed per-episode results can be found in [eval/eval_info.json](./eval/eval_info.json).
|
| 95 |
+
|
| 96 |
+
<!-- EVAL_RESULTS_END -->
|