strangetcy commited on
Commit
3fa02df
·
verified ·
1 Parent(s): af58bcc

Upload PPO LunarLander-v2 trained agent

Browse files
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: 289.23 +/- 16.51
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 0x7d886c343ac0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d886c343b50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d886c343be0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d886c343c70>", "_build": "<function ActorCriticPolicy._build at 0x7d886c343d00>", "forward": "<function ActorCriticPolicy.forward at 0x7d886c343d90>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d886c343e20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d886c343eb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d886c343f40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d886c34c040>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d886c34c0d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d886c34c160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d886c2fc480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1723038494604042493, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 476, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 4096, "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": 10, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "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 sha256:45d51923e2235b073b781664cbb0be04a22f05dc717d9196bde696dc81e124e4
3
+ size 147953
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 0x7d886c343ac0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d886c343b50>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d886c343be0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d886c343c70>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7d886c343d00>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7d886c343d90>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d886c343e20>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d886c343eb0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7d886c343f40>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d886c34c040>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d886c34c0d0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d886c34c160>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7d886c2fc480>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 3014656,
25
+ "_total_timesteps": 3000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1723038494604042493,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.004885333333333408,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHIQ1mz0HyGMAWyUS7SMAXSUR0CvSDffGdZrdX2UKGgGR0B0bhSzgMtsaAdLxWgIR0CvSHiHymQ9dX2UKGgGR0BwMIcdYGMXaAdLxGgIR0CvSIHCwbEQdX2UKGgGR0By6cqwyIpIaAdL32gIR0CvSMJlSS/1dX2UKGgGR0Bw+517pmmMaAdLsmgIR0CvSMx0EHMVdX2UKGgGR0BzFTVSXMQmaAdLx2gIR0CvSPcfV7QcdX2UKGgGR0ByttsP8Q7LaAdLtmgIR0CvSP3tBv74dX2UKGgGR0BywSfjCHh1aAdL0GgIR0CvSRSZrpJPdX2UKGgGR0Bu100YTCcgaAdLq2gIR0CvSRiDdxhldX2UKGgGR0BylAZOzposaAdLtGgIR0CvSVHim2srdX2UKGgGR0BxCFy0a6z3aAdLwGgIR0CvSXNutOmBdX2UKGgGR0By8nK/20zCaAdLw2gIR0CvSXyDyvs7dX2UKGgGR0BxumX4TK1YaAdLlWgIR0CvSaJtrKvFdX2UKGgGR0BzSVGI9C/oaAdLrWgIR0CvSa0rTYukdX2UKGgGR0BxLq3I+4b0aAdL12gIR0CvSbQ9JSR9dX2UKGgGR0BxbhCrtE5RaAdLrWgIR0CvScaPbO/tdX2UKGgGR0BxVRjd56dEaAdLuWgIR0CvScrpJPIodX2UKGgGR0BySJGc4HX3aAdLsWgIR0CvSitWluWKdX2UKGgGR0Bx6ZlNDc/MaAdLvGgIR0CvSj3yRSxadX2UKGgGR0Bx68rpaA4GaAdLv2gIR0CvSpDkdV/+dX2UKGgGR0Bw+fmwJPZaaAdLxmgIR0CvSpouGsV+dX2UKGgGR0BxrzzFuNxVaAdLs2gIR0CvSqPuw5eadX2UKGgGR0BxHY8r7O3VaAdLx2gIR0CvSvWiL2pRdX2UKGgGR0B0RmV/tpmFaAdL12gIR0CvSv8QAdXDdX2UKGgGR0BxcGyon8baaAdLzWgIR0CvSwllK9PDdX2UKGgGR0Bwv2ZBsyi3aAdLp2gIR0CvSw6dDpkgdX2UKGgGR0ByF2po9LYgaAdLx2gIR0CvSzhdld1MdX2UKGgGR0BxERVjqfOEaAdLrGgIR0CvS0vH1e0HdX2UKGgGR0Bw7rKMefZmaAdLuWgIR0CvS5qB/ZuidX2UKGgGR0Bzn4WcjJMhaAdLxmgIR0CvS6L5IpYtdX2UKGgGR0Bzc0cJdB0IaAdL0mgIR0CvS7hxgiNbdX2UKGgGR0BzofrQgLZ0aAdL12gIR0CvS+LxZuAJdX2UKGgGR0Byko8B+4LDaAdL/GgIR0CvS+2aMJhOdX2UKGgGR0ByLQgr6LwXaAdLyGgIR0CvTCWcBltkdX2UKGgGR0BxwHVUdaMaaAdLzWgIR0CvTETlcQiBdX2UKGgGR0ByF1YgaFVUaAdLtGgIR0CvTFp9qk/KdX2UKGgGR0Bx+b5HmRvFaAdLu2gIR0CvTHPddmg8dX2UKGgGR0Byp6rT6SDAaAdLw2gIR0CvTJEpRXOodX2UKGgGR0Bw8+5H3DekaAdLsWgIR0CvTK5gXuVpdX2UKGgGR0BynwNtqHoHaAdLsmgIR0CvTLpxvNu+dX2UKGgGR0ByzKifxtpFaAdLuWgIR0CvTNlD4QBgdX2UKGgGR0Byg2V2Rq46aAdLvWgIR0CvTOuVxCIDdX2UKGgGR0By+C8Yht+DaAdLs2gIR0CvTRBMJx//dX2UKGgGR0BxLzM6ij+KaAdLwmgIR0CvTSFpoK2KdX2UKGgGR0Bx9bLV4HHFaAdLq2gIR0CvTWOO801qdX2UKGgGR0ByuwekpI+XaAdLyGgIR0CvTZFbVz6rdX2UKGgGR0BwRKagElmfaAdLs2gIR0CvTaOCGvfTdX2UKGgGR0By6yk9ECvHaAdL2mgIR0CvTccm0E5idX2UKGgGR0B0LTCuU2UCaAdLv2gIR0CvTc2S2Yv4dX2UKGgGR0ByEpV94NZvaAdLuWgIR0CvTfi6H0sfdX2UKGgGR0BxszxYq5LAaAdLpWgIR0CvTfw+UyHmdX2UKGgGR0By3idtl7MQaAdLsWgIR0CvTgRJVbRndX2UKGgGR0BxdbGWD6FeaAdLtmgIR0CvTkBIvrWzdX2UKGgGR0BzNRDgIhQnaAdLv2gIR0CvTnioS+QEdX2UKGgGR0BxNAa2nbZfaAdLuGgIR0CvToU9QoCudX2UKGgGR0ByPVTzd1uBaAdLwmgIR0CvTq23KB/adX2UKGgGR0BzBtpGnXNDaAdLtGgIR0CvTrad+XqrdX2UKGgGR0Bwj7aCcwxnaAdLxGgIR0CvTs9rwe/6dX2UKGgGR0Bx51p8F6iTaAdLrmgIR0CvTs6/7BO6dX2UKGgGR0BGE9FF2FFlaAdLbWgIR0CvTum4RVZLdX2UKGgGR0Bzn7+MqBmPaAdLxWgIR0CvTxoxQBPsdX2UKGgGR0By2+t/4IrwaAdLrGgIR0CvT0vAGjbjdX2UKGgGR0BzSmbH6uW9aAdLo2gIR0CvT2pjMFEBdX2UKGgGR0ByRgXJo0yhaAdLjmgIR0CvT3Io3JgcdX2UKGgGR0BylA8EFGG3aAdL02gIR0CvT8FmFrVOdX2UKGgGR0BzAaEAYHgQaAdLumgIR0CvT9t7a7EpdX2UKGgGR0BzkjkOqebvaAdLvmgIR0CvT+L3TNMXdX2UKGgGR0B0HNGz8gp0aAdL/WgIR0CvT/BePaL5dX2UKGgGR0Bx+qXLNfPYaAdLqWgIR0CvUDkeZG8VdX2UKGgGR0Byr9QizLOiaAdLx2gIR0CvUEVrRBu5dX2UKGgGR0By+YVYZEUkaAdLtmgIR0CvUE/MnqmkdX2UKGgGR0BwUolMRHwxaAdLoWgIR0CvULN/FzdUdX2UKGgGR0BxzinQ6ZH/aAdLvGgIR0CvUMdFfAsTdX2UKGgGR0BzyJzDGcWkaAdLyWgIR0CvUM6oESuhdX2UKGgGR0BzjhWilBQfaAdL22gIR0CvUNwnQY1pdX2UKGgGR0BypR5mh/RWaAdL12gIR0CvUNtIkJKKdX2UKGgGR0BylnhHbypaaAdL7GgIR0CvUSpFTefqdX2UKGgGR0BzCeOn2qT9aAdLt2gIR0CvUT16E8JVdX2UKGgGR0Bx+I84gieNaAdLzGgIR0CvUVR2r4nGdX2UKGgGR0BxwUzImw7laAdLvGgIR0CvUZ1ktmL+dX2UKGgGR0Bvpq1XvH94aAdLuWgIR0CvUbW1MM7VdX2UKGgGR0BzsoliSaE0aAdLvmgIR0CvUbvX05EMdX2UKGgGR0B0FKsr/bTMaAdL52gIR0CvUbx9w3o+dX2UKGgGR0BzPQD4gzP9aAdL1WgIR0CvUgf7JnxsdX2UKGgGR0BvDHPgNwzdaAdLsGgIR0CvUgeKjzqbdX2UKGgGR0Bw69/OMVDbaAdLwmgIR0CvUioQ4CIUdX2UKGgGR0Bxwc8uBczJaAdLy2gIR0CvUjUsvqTsdX2UKGgGR0ByCULqlgtwaAdLsWgIR0CvUm8z67/XdX2UKGgGR0BF6VvVEuxsaAdLdGgIR0CvUnOH31zydX2UKGgGR0BxdcvTPSlWaAdLrmgIR0CvUorOqvNedX2UKGgGR0BygJSEUTL4aAdLxWgIR0CvUsIAn2IwdX2UKGgGR0BzEO9oN/e+aAdLy2gIR0CvUsP3BYV7dX2UKGgGR0ByHlKSPluFaAdLp2gIR0CvUtZSWJJodX2UKGgGR0BxFVg+hXbNaAdLtGgIR0CvUuGHYYixdX2UKGgGR0BykA7eVLSNaAdLomgIR0CvUyvldTo/dX2UKGgGR0Byia2phnanaAdL+mgIR0CvUzHHNorXdX2UKGgGR0BwdnP0I1LraAdLrWgIR0CvU2CL/CIldX2UKGgGR0BxCeN3np0PaAdLuWgIR0CvU3cRlHz6dX2UKGgGR0BxHFky1uzhaAdLzWgIR0CvU6vw3HaOdX2UKGgGR0BxcKhPCVKPaAdLsGgIR0CvU7DPv8ZUdWUu"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 476,
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 16,
80
+ "n_steps": 4096,
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": 10,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
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:cf504e61f3d6c23f7e5c4402c5ac0d278657ddaac2c0b978b18c7331da5564aa
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:df4218ae703ea85ba01ae61272592e2f2784486887660d970a112a689183f47a
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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.3.1+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.26.4
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (169 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 289.22672029409387, "std_reward": 16.505719799138284, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-08-07T14:54:52.450933"}