Initial commit
Browse files- README.md +4 -4
- args.yml +3 -1
- dqn-SpaceInvadersNoFrameskip-v4.zip +2 -2
- dqn-SpaceInvadersNoFrameskip-v4/data +0 -0
- dqn-SpaceInvadersNoFrameskip-v4/policy.optimizer.pth +2 -2
- dqn-SpaceInvadersNoFrameskip-v4/policy.pth +2 -2
- dqn-SpaceInvadersNoFrameskip-v4/pytorch_variables.pth +2 -2
- dqn-SpaceInvadersNoFrameskip-v4/system_info.txt +2 -2
- replay.mp4 +2 -2
- results.json +1 -1
- train_eval_metrics.zip +2 -2
README.md
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@@ -16,7 +16,7 @@ model-index:
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type: SpaceInvadersNoFrameskip-v4
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metrics:
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- type: mean_reward
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-
value:
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name: mean_reward
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verified: false
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---
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@@ -43,13 +43,13 @@ pip install rl_zoo3
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```
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# Download model and save it into the logs/ folder
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-
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga
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python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
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```
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python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga
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python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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@@ -57,7 +57,7 @@ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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# Upload the model and generate video (when possible)
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python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga
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```
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## Hyperparameters
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type: SpaceInvadersNoFrameskip-v4
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metrics:
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- type: mean_reward
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+
value: 320.00 +/- 86.46
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name: mean_reward
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verified: false
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---
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```
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# Download model and save it into the logs/ folder
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+
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga PMOLODO -f logs/
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python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
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```
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+
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga PMOLODO -f logs/
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python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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```
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python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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# Upload the model and generate video (when possible)
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+
python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga PMOLODO
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```
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## Hyperparameters
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args.yml
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- SpaceInvadersNoFrameskip-v4
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- - env_kwargs
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- null
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- - eval_episodes
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- 5
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- - eval_freq
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- - save_replay_buffer
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- false
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- - seed
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-
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- - storage
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- null
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- - study_name
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- SpaceInvadersNoFrameskip-v4
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- - env_kwargs
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- - eval_env_kwargs
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- null
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- - eval_episodes
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- 5
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- - eval_freq
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- - save_replay_buffer
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- false
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- - seed
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- 1432731666
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- - storage
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- null
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- - study_name
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dqn-SpaceInvadersNoFrameskip-v4.zip
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dqn-SpaceInvadersNoFrameskip-v4/data
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dqn-SpaceInvadersNoFrameskip-v4/policy.optimizer.pth
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dqn-SpaceInvadersNoFrameskip-v4/system_info.txt
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-
- OS: Linux-
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- Python: 3.10.12
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- Stable-Baselines3: 2.3.2
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-
- PyTorch: 2.
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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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- OS: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.35 # 1 SMP Fri Apr 2 22:23:49 UTC 2021
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- Stable-Baselines3: 2.3.2
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- PyTorch: 2.0.0.post101
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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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replay.mp4
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results.json
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{"mean_reward":
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train_eval_metrics.zip
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