Initial commit
Browse files- DQN SpaceInvaders.zip +3 -0
- DQN SpaceInvaders/_stable_baselines3_version +1 -0
- DQN SpaceInvaders/data +0 -0
- DQN SpaceInvaders/policy.optimizer.pth +3 -0
- DQN SpaceInvaders/policy.pth +3 -0
- DQN SpaceInvaders/pytorch_variables.pth +3 -0
- DQN SpaceInvaders/system_info.txt +9 -0
- README.md +37 -0
- config.json +0 -0
- replay.mp4 +0 -0
- results.json +1 -0
DQN SpaceInvaders.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:fa2393498aa100fca36748cb3a88b0090a94cfb585a5b3622d0f6ebebd5e4e7e
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size 186659113
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DQN SpaceInvaders/_stable_baselines3_version
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2.3.2
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DQN SpaceInvaders/data
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DQN SpaceInvaders/policy.optimizer.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:916a29382567479536d27d5f0e63a0b0cdd53b6b39a25422c9706823a850e858
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size 92919100
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DQN SpaceInvaders/policy.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:e7a5560eeb39c0d4e51a5ffd75c4d48acd6e5459bbdab53ea74550944666e972
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size 92918426
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DQN SpaceInvaders/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
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size 864
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DQN SpaceInvaders/system_info.txt
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- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
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- Python: 3.10.12
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- Stable-Baselines3: 2.3.2
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- PyTorch: 2.2.1+cu121
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- GPU Enabled: False
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- Numpy: 1.25.2
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- Cloudpickle: 2.2.1
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- Gymnasium: 0.29.1
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- OpenAI Gym: 0.25.2
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README.md
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---
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library_name: stable-baselines3
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tags:
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- SpaceInvadersNoFrameskip-v4
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- deep-reinforcement-learning
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- reinforcement-learning
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- stable-baselines3
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model-index:
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- name: DQN
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results:
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- task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: SpaceInvadersNoFrameskip-v4
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type: SpaceInvadersNoFrameskip-v4
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metrics:
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- type: mean_reward
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value: 258.50 +/- 169.00
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name: mean_reward
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verified: false
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---
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# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
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This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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TODO: Add your code
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```python
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from stable_baselines3 import ...
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from huggingface_sb3 import load_from_hub
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...
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```
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config.json
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replay.mp4
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results.json
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{"mean_reward": 258.5, "std_reward": 168.9977810505215, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2024-05-18T01:02:39.398421"}
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