Initial commit
Browse files- .gitattributes +1 -0
- README.md +67 -0
- args.yml +75 -0
- config.yml +25 -0
- env_kwargs.yml +1 -0
- ppo-SpaceInvadersNoFrameskip-v4.zip +3 -0
- ppo-SpaceInvadersNoFrameskip-v4/_stable_baselines3_version +1 -0
- ppo-SpaceInvadersNoFrameskip-v4/data +0 -0
- ppo-SpaceInvadersNoFrameskip-v4/policy.optimizer.pth +3 -0
- ppo-SpaceInvadersNoFrameskip-v4/policy.pth +3 -0
- ppo-SpaceInvadersNoFrameskip-v4/pytorch_variables.pth +3 -0
- ppo-SpaceInvadersNoFrameskip-v4/system_info.txt +7 -0
- replay.mp4 +3 -0
- results.json +1 -0
- train_eval_metrics.zip +3 -0
.gitattributes
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@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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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: PPO
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results:
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- metrics:
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- type: mean_reward
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value: 1025.50 +/- 612.32
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name: mean_reward
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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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---
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# **PPO** Agent playing **SpaceInvadersNoFrameskip-v4**
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This is a trained model of a **PPO** agent playing **SpaceInvadersNoFrameskip-v4**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
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and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
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The RL Zoo is a training framework for Stable Baselines3
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reinforcement learning agents,
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with hyperparameter optimization and pre-trained agents included.
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## Usage (with SB3 RL Zoo)
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RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
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SB3: https://github.com/DLR-RM/stable-baselines3<br/>
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SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
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```
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# Download model and save it into the logs/ folder
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python -m utils.load_from_hub --algo ppo --env SpaceInvadersNoFrameskip-v4 -orga Corianas -f logs/
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python enjoy.py --algo ppo --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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## Training (with the RL Zoo)
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```
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python train.py --algo ppo --env SpaceInvadersNoFrameskip-v4 -f logs/
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# Upload the model and generate video (when possible)
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python -m utils.push_to_hub --algo ppo --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga Corianas
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```
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## Hyperparameters
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```python
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OrderedDict([('batch_size', 256),
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('clip_range', 'lin_0.1'),
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('ent_coef', 0.01),
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('env_wrapper',
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['stable_baselines3.common.atari_wrappers.AtariWrapper']),
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('frame_stack', 4),
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('learning_rate', 'lin_2.5e-4'),
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('n_envs', 8),
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('n_epochs', 4),
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('n_steps', 128),
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('n_timesteps', 10000000.0),
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('policy', 'CnnPolicy'),
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('vf_coef', 0.5),
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('normalize', False)])
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```
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args.yml
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!!python/object/apply:collections.OrderedDict
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- - - algo
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- ppo
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- - device
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+
- auto
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- - env
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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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- 25000
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- - gym_packages
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- []
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- - hyperparams
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- null
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- - log_folder
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- /content/drive/MyDrive/ML
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- - log_interval
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- -1
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+
- - max_total_trials
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- null
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- - n_eval_envs
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- 1
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- - n_evaluations
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- null
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- - n_jobs
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- 1
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- - n_startup_trials
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- 10
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- - n_timesteps
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- -1
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- - n_trials
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- 500
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- - no_optim_plots
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- false
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- - num_threads
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- -1
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- - optimization_log_path
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- null
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- - optimize_hyperparameters
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- false
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- - pruner
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- median
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- - sampler
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- tpe
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- - save_freq
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- 250000
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- - save_replay_buffer
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- false
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- - seed
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- 1899677552
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- - storage
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- null
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- - study_name
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- null
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- - tensorboard_log
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- runs/SpaceInvadersNoFrameskip-v4__ppo__1899677552__1656293428
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- - track
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- true
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- - trained_agent
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- ''
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- - truncate_last_trajectory
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- true
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- - uuid
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- false
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- - vec_env
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- dummy
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- - verbose
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- 1
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- - wandb_entity
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- null
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- - wandb_project_name
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- SpaceInvaders
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config.yml
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!!python/object/apply:collections.OrderedDict
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- - - batch_size
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- 256
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- - clip_range
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- lin_0.1
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- - ent_coef
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- 0.01
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+
- - env_wrapper
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9 |
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- - stable_baselines3.common.atari_wrappers.AtariWrapper
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- - frame_stack
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- 4
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- - learning_rate
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- lin_2.5e-4
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- - n_envs
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- 8
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- - n_epochs
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- 4
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+
- - n_steps
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- 128
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- - n_timesteps
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- 10000000.0
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+
- - policy
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- CnnPolicy
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- - vf_coef
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- 0.5
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env_kwargs.yml
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{}
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ppo-SpaceInvadersNoFrameskip-v4.zip
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:1666fec1b82df3ac7b28a036df3326f086f3814f885efa0fd071951dc6d464cf
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size 20439044
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ppo-SpaceInvadersNoFrameskip-v4/_stable_baselines3_version
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1.5.1a8
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ppo-SpaceInvadersNoFrameskip-v4/data
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See raw diff
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ppo-SpaceInvadersNoFrameskip-v4/policy.optimizer.pth
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:b5b6ea9b1e646d387b7b2473f4f010dab1197a5bdb1bf8ec2e4c2d4faf3fda02
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size 13508317
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ppo-SpaceInvadersNoFrameskip-v4/policy.pth
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:4b97f4969d2ece84b7d7489f40e7030e88f7238d3588848fb69c163cb1c4c256
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size 6755009
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ppo-SpaceInvadersNoFrameskip-v4/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
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size 431
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ppo-SpaceInvadersNoFrameskip-v4/system_info.txt
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OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
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Python: 3.7.13
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Stable-Baselines3: 1.5.1a8
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PyTorch: 1.11.0+cu113
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GPU Enabled: True
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Numpy: 1.21.6
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Gym: 0.21.0
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replay.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:3acb90cf9aacc2cc725d1f5b0128ccbb501227ae9cf72127c012ed6c2f51ceef
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size 198027
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results.json
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{"mean_reward": 1025.5, "std_reward": 612.3171155536974, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2022-06-27T08:23:15.023396"}
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train_eval_metrics.zip
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:e9a6a3c95c109f0ad08bba5cb446474edda68508651a5d381552e0fd24c6060a
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+
size 303196
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