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sac-PandaReachDense-v3
bestdive/sac-PandaReachDense-v3
sac-PandaReachDense-v3 is a reinforcement learning model from bestdive. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3. The card lists the license as mit.
Kay Zheng's Unit 6 coursework, trained from scratch with AI coding assistance. Stable Baselines3 2.3.2, Gymnasium 0.29.1, panda-gym 3.0.7, pybullet 3.2.7, seed 42. Training: 20000 environment steps, CPU. Held-out eval…
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At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- License
- mit
- Access
- Public
- Created
- Sep 10, 2026
- Updated
- Sep 10, 2026
- SHA
- 288eebec
Model card
From the Hugging Face model README
SAC PandaReachDense-v3
Kay Zheng's Unit 6 coursework, trained from scratch with AI coding assistance. Stable Baselines3 2.3.2, Gymnasium 0.29.1, panda-gym 3.0.7, pybullet 3.2.7, seed 42. Training: 20000 environment steps, CPU. Held-out evaluation: 100 episodes, seeds 100000–100099. Mean reward -0.2263398146163672, std 0.1048106702883708, mean minus std -0.331150. Full evaluation rewards are in evaluation.json.
Reproduce with python train_panda.py; load with SAC.load('model.zip').
On current macOS SDK, building pybullet 3.2.7 required CFLAGS='-Dfdopen=fdopen' to prevent an obsolete bundled zlib macro from shadowing the system declaration.
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- License
- mit
- Created
- Sep 10, 2026
- Updated
- Sep 10, 2026