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reinforce-CartPole-v1
bestdive/reinforce-CartPole-v1
reinforce-CartPole-v1 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. The card lists the license as mit.
Trained from scratch for Kay Zheng's Hugging Face Deep RL coursework with AI coding assistance. REINFORCE, reward-to-go, batch baseline, 64-unit tanh policy network. Training: 166816 steps with seed 42. Validation see…
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Updated Sep 10, 2026
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.pt4.1 KB · 39%
At a glance
- Task
- Reinforcement Learning
- License
- mit
- Access
- Public
- Created
- Sep 10, 2026
- Updated
- Sep 10, 2026
- SHA
- eb1d0c0a
Model card
From the Hugging Face model README
REINFORCE CartPole-v1
Trained from scratch for Kay Zheng's Hugging Face Deep RL coursework with AI coding assistance. REINFORCE, reward-to-go, batch baseline, 64-unit tanh policy network. Training: 166816 steps with seed 42. Validation seeds 50000–50029. Held-out evaluation: 100 episodes, seeds 100000–100099, greedy policy. Mean reward 497.1, standard deviation 17.15546560137614, mean minus std 479.944534.
Reproduce
Install gymnasium==0.29.1, numpy, torch. Run python train_cartpole.py.
policy.pt contains the trained state dictionary. Evaluation rewards are in evaluation.json.
- Task
- Reinforcement Learning
- License
- mit
- Created
- Sep 10, 2026
- Updated
- Sep 10, 2026