HaythamB commited on
Commit
7dd517a
1 Parent(s): f6dcce3
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 231.39 +/- 75.79
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7ded40777c70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ded40777d00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ded40777d90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ded40777e20>", "_build": "<function ActorCriticPolicy._build at 0x7ded40777eb0>", "forward": "<function ActorCriticPolicy.forward at 0x7ded40777f40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ded4078c040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ded4078c0d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ded4078c160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ded4078c1f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ded4078c280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ded4078c310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ded40788640>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1703541551225292613, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGZAUr1c32u63Yimu8HzjDypKwo8Fsh0vQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVMgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQERqgow22oiMAWyUTQUBjAF0lEdAn7oiHymQ83V9lChoBkdAb/XGpda+vmgHTUMBaAhHQJ+8GdoWYWt1fZQoaAZHQHBGsc2itaJoB01UAWgIR0Cfv409hZyNdX2UKGgGR0BtJ4GwA2hqaAdNHgFoCEdAn8Fh1oxpL3V9lChoBkdAcHKIatLcsWgHTS4BaAhHQJ/DcoTfzjF1fZQoaAZHQG8zqebutwJoB00RAWgIR0Cfxm0UoKD1dX2UKGgGR0A5HYxL0z0paAdNCwFoCEdAn8g3oLXtjXV9lChoBkdAbj9S/CZWrGgHTTEBaAhHQJ/K4p3HJcR1fZQoaAZHQHBOz3AVO9FoB01NAWgIR0CfzQR8+iaidX2UKGgGR0BvPtqgyuZDaAdNJgFoCEdAn9A9tALRbHV9lChoBkdAbhUEal1r7GgHTc4BaAhHQJ/TUupS75F1fZQoaAZHwCcwfU4JeE9oB0uUaAhHQJ/UTZoPCl91fZQoaAZHwDFivbGm1ploB0uhaAhHQJ/Wnub7TDx1fZQoaAZHQGLHRRMvh61oB03oA2gIR0Cf36drO7g9dX2UKGgGR0BwleQp4KQaaAdNTgFoCEdAn+JeyRjjJnV9lChoBkdAcJBRNh3JP2gHTUgBaAhHQJ/lCLpA2Q51fZQoaAZHQHD3J9uxbB5oB00KAWgIR0Cf5w/FzdULdX2UKGgGR0BBsuearmyPaAdL82gIR0Cf6eDwpe/pdX2UKGgGR0BtP9F6Rhc8aAdNQgFoCEdAn+veuV5a/3V9lChoBkdAYOoQZn+Q2mgHTegDaAhHQJ/zj5Lytmt1fZQoaAZHQG6yajesPrhoB01PAWgIR0Cf9bDn/1g6dX2UKGgGR0Bv5zwazeGgaAdNLQFoCEdAn/jTXrdFfHV9lChoBkdAcki9Dx9XtGgHTUQBaAhHQJ/64Gr0aqF1fZQoaAZHQEtksZHd43ZoB00PAWgIR0Cf/I8wHqu9dX2UKGgGR0BwvGveP7vYaAdNOAFoCEdAn/6CN0eU6nV9lChoBkdAbqpIJ7b+LmgHTUQBaAhHQKAA8GdI5HV1fZQoaAZHQG9zKGDcuapoB03cAWgIR0CgAnrfUF0QdX2UKGgGR0ByKij2zv7WaAdNZAFoCEdAoARAY3vQW3V9lChoBkdAcpg+tbLU1GgHTV4BaAhHQKAFayZa3Zx1fZQoaAZHQG47koWpIc1oB00OAWgIR0CgBkh6jWTYdX2UKGgGR0Bst4m1IAfdaAdNEQFoCEdAoAcrb1yvLXV9lChoBkdAcP7BqsU7CGgHTa4BaAhHQKAJw94eLeh1fZQoaAZHQG7clWn0kGBoB0v5aAhHQKAKy7vG6wt1fZQoaAZHQHElHbypaRpoB00iAWgIR0CgC/KHO8kEdX2UKGgGR0BxsMWac7QtaAdNVwFoCEdAoA4Xyup0fnV9lChoBkdAcW4ZtelbeWgHTVEBaAhHQKAPKa/ATIx1fZQoaAZHQHAzGetjkMloB00iAWgIR0CgEBR51Ng0dX2UKGgGR0ByOEHs1KoRaAdNqgFoCEdAoBIc/dIoVnV9lChoBkdAcDJ5H3Dej2gHTRsBaAhHQKATESElE7Z1fZQoaAZHQHDuXyy2QXBoB01UAWgIR0CgFChMSK3vdX2UKGgGR0BtuezhP0qZaAdNGgFoCEdAoBW+wC8vmHV9lChoBkdAUXW9QGfPHGgHTRMBaAhHQKAWo/nGKht1fZQoaAZHQHEDDINmUW5oB00wAWgIR0CgF6vOyE+QdX2UKGgGR0Bu8xtgrpaBaAdNHAFoCEdAoBiT961LJ3V9lChoBkdAbzEqm0mdAmgHTSMBaAhHQKAaHy1/lQx1fZQoaAZHQGDBwwK0D2doB03oA2gIR0CgHh6BZpztdX2UKGgGR0A/bmXPZ7HAaAdL8WgIR0CgHuD8+A3DdX2UKGgGR0BwFrYao/A1aAdNfwFoCEdAoCAi2a2F4HV9lChoBkdAPsS+UQkHEGgHS7poCEdAoCFjR2KVIXV9lChoBkdAOrQSamXPaGgHS/toCEdAoCJztoi9qXV9lChoBkdAQ2PM8ox59mgHTQIBaAhHQKAjjzp5eJJ1fZQoaAZHQE8s+s5n14BoB00QAWgIR0CgJKZBkZrIdX2UKGgGR0BwBpnPE87qaAdLwmgIR0CgJXCdJ8OTdX2UKGgGR0Bwt/HU+cH4aAdNOQFoCEdAoCePsPatcXV9lChoBkdAcL2gy/KyOmgHTQoBaAhHQKAok2vStvJ1fZQoaAZHQHC4FjVhCt1oB00MAWgIR0CgKXQzDXOGdX2UKGgGR0BFGqOktVaPaAdL6mgIR0CgKtBf0EowdX2UKGgGR0BxoqMo+fRNaAdNTQFoCEdAoCvrMaCL/HV9lChoBkdAcOOpsoDxLGgHTWUBaAhHQKAtEz544ZN1fZQoaAZHQG/s8J+lTFVoB01GAWgIR0CgLrZ31SOzdX2UKGgGR0Ahn0h/y5I6aAdLsWgIR0CgLz5dWyTqdX2UKGgGR0BwG7wlSjxkaAdNMQFoCEdAoDAxqVQhwHV9lChoBkdAcShwe/5+IGgHTSYBaAhHQKAxGd5prUN1fZQoaAZHQG9QN7BwdbRoB00tAWgIR0CgMrI24uscdX2UKGgGR0BN0PKEFnqWaAdL12gIR0CgM1tyHVPOdX2UKGgGR0BsfWEmICU5aAdNigFoCEdAoDSfNmlImXV9lChoBkdARZrJfYzzmWgHS9poCEdAoDVJtxdY4nV9lChoBkdAbVENFz+3pmgHTSUBaAhHQKA20skIHC51fZQoaAZHQDRTFUADJU5oB0vVaAhHQKA3feGfwql1fZQoaAZHQG9d/YraufVoB00aAWgIR0CgOGlz2exwdX2UKGgGR0Bn+FnEl3QlaAdNTQFoCEdAoDmF3t8eCHV9lChoBkdAOhmfseGO/GgHS91oCEdAoDrmRoysS3V9lChoBkdAb+iExIre7GgHS/toCEdAoDuzLW7OFHV9lChoBkdAcFNg+QlrumgHTUQBaAhHQKA9ArK/2011fZQoaAZHQHLI2G21D0FoB01zAWgIR0CgP5hMajvedX2UKGgGR0BAxqFZgXuWaAdL32gIR0CgQIR8twrEdX2UKGgGR0BsqL349HMEaAdNJQFoCEdAoEHKoVEeAHV9lChoBkdAKU92ovSMLmgHS65oCEdAoEKUkKNQ03V9lChoBkdAcCfAWSEDhmgHTXkDaAhHQKBGJxPwd811fZQoaAZHQG7Z2QOnVG1oB00SAWgIR0CgRwnDBMzudX2UKGgGR0BvffUH6dlNaAdNLAFoCEdAoEibt7a7E3V9lChoBkdAcJ6Lf1pTM2gHTRMBaAhHQKBJhL6k6911fZQoaAZHQHHVeafBeoloB005AWgIR0CgSoBK15SndX2UKGgGR0Br2tX1anrIaAdNIQFoCEdAoEwdlkH2RXV9lChoBkdAbfsFEAo5P2gHTWsBaAhHQKBNTw++ueV1fZQoaAZHQHAowTVUdaNoB00/AWgIR0CgToGXPZ7HdX2UKGgGR0Bt8orlNlAeaAdNJwFoCEdAoFCZe7cwg3V9lChoBkdAcIbeKKpDNWgHTWABaAhHQKBSHm6oVEd1fZQoaAZHQHF1tR3u/lBoB01FAWgIR0CgU3Oyu6mPdX2UKGgGR0BDkccU/OdHaAdLv2gIR0CgVDX6hxo7dX2UKGgGR0BwAXQQcxTLaAdNIQFoCEdAoFZV4s3AEnV9lChoBkdAb5h2HtWuHWgHTVQBaAhHQKBX+8EFGG51fZQoaAZHQHHYif16E8JoB02rAWgIR0CgWdLLhaTwdX2UKGgGR0BvSs/r0J4TaAdNNQFoCEdAoFvgJE6T4nV9lChoBkdAcSNdq+JxemgHTYIBaAhHQKBdgPtlZox1fZQoaAZHQGMDh1cMVlBoB03oA2gIR0CgYXhPKuB+dX2UKGgGR0Bvb0RHww0waAdNAQFoCEdAoGJWnjyWiXV9lChoBkdAbrGE1VHWjGgHTS4BaAhHQKBj+yv9tMx1fZQoaAZHQHHYKJZW7vpoB01DAWgIR0CgZRIHC4z8dX2UKGgGR0BxDToxHoX9aAdNEgFoCEdAoGX9D0Dlo3VlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3908, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9393a2018fd430c6d3998c37f46fd44bb661b86723b51e462df54cda07f2987c
3
+ size 147636
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7ded40777c70>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ded40777d00>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ded40777d90>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ded40777e20>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ded40777eb0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ded40777f40>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ded4078c040>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ded4078c0d0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ded4078c160>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ded4078c1f0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ded4078c280>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ded4078c310>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7ded40788640>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1000448,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1703541551225292613,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGZAUr1c32u63Yimu8HzjDypKwo8Fsh0vQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.00044800000000000395,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 3908,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "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",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": "Generator(PCG64)"
78
+ },
79
+ "n_envs": 1,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null,
95
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8de9354da80e17d4ee3bd2b49eef772be67522f307537c575c9b94901eb35b8e
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:67cc9062c8cc457d8f7d1014880772b6b075536585415b3bb166a1713d8a105d
3
+ size 43762
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.23.5
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (145 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 231.3873787, "std_reward": 75.78514625178978, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-25T22:34:57.173135"}