mlwithrakesh commited on
Commit
273a904
1 Parent(s): 7f6e9be

Upload PPO LunarLander-v2 trained agent

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 259.74 +/- 23.11
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 265.90 +/- 17.53
20
  name: mean_reward
21
  verified: false
22
  ---
config.json CHANGED
@@ -1 +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 0x7c89a0382290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c89a0382320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c89a03823b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c89a0382440>", "_build": "<function ActorCriticPolicy._build at 0x7c89a03824d0>", "forward": "<function ActorCriticPolicy.forward at 0x7c89a0382560>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c89a03825f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c89a0382680>", "_predict": "<function ActorCriticPolicy._predict at 0x7c89a0382710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c89a03827a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c89a0382830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c89a03828c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c89a04f82c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700914015830938945, "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": -0.015808000000000044, "_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": 248, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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-5.15.133+-x86_64-with-glibc2.35 # 1 SMP Wed Nov 8 17:30:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.0", "GPU Enabled": "True", "Numpy": "1.24.3", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}
 
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 0x7f0e8cce9f30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0e8cce9fc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0e8ccea050>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0e8ccea0e0>", "_build": "<function ActorCriticPolicy._build at 0x7f0e8ccea170>", "forward": "<function ActorCriticPolicy.forward at 0x7f0e8ccea200>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0e8ccea290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0e8ccea320>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0e8ccea3b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0e8ccea440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0e8ccea4d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0e8ccea560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f0e8cc91980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700914015830938945, "learning_rate": 0.0, "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": -0.015808000000000044, "_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": 248, "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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:7fe6e4fa572ccbf8523e942f113886ce471febf2f7f9c27800f1f19114d5c138
3
- size 146656
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:825a253f79b7b5fb58f6dc25692144629e29dac110b77c4b9707f875daf6231e
3
+ size 147879
ppo-LunarLander-v2/data CHANGED
@@ -4,20 +4,20 @@
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 0x7c89a0382290>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c89a0382320>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c89a03823b0>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c89a0382440>",
11
- "_build": "<function ActorCriticPolicy._build at 0x7c89a03824d0>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x7c89a0382560>",
13
- "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c89a03825f0>",
14
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c89a0382680>",
15
- "_predict": "<function ActorCriticPolicy._predict at 0x7c89a0382710>",
16
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c89a03827a0>",
17
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c89a0382830>",
18
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c89a03828c0>",
19
  "__abstractmethods__": "frozenset()",
20
- "_abc_impl": "<_abc._abc_data object at 0x7c89a04f82c0>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
@@ -27,7 +27,7 @@
27
  "seed": null,
28
  "action_noise": null,
29
  "start_time": 1700914015830938945,
30
- "learning_rate": 0.0003,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
@@ -52,9 +52,24 @@
52
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
  },
54
  "_n_updates": 248,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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]",
@@ -69,7 +84,7 @@
69
  },
70
  "action_space": {
71
  ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
- ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
73
  "n": "4",
74
  "start": "0",
75
  "_shape": [],
@@ -77,23 +92,8 @@
77
  "_np_random": null
78
  },
79
  "n_envs": 16,
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
  }
 
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 0x7f0e8cce9f30>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0e8cce9fc0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0e8ccea050>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0e8ccea0e0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f0e8ccea170>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f0e8ccea200>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0e8ccea290>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0e8ccea320>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f0e8ccea3b0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0e8ccea440>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0e8ccea4d0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0e8ccea560>",
19
  "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f0e8cc91980>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
 
27
  "seed": null,
28
  "action_noise": null,
29
  "start_time": 1700914015830938945,
30
+ "learning_rate": 0.0,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
 
52
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
  },
54
  "_n_updates": 248,
55
+ "n_steps": 1024,
56
+ "gamma": 0.999,
57
+ "gae_lambda": 0.98,
58
+ "ent_coef": 0.01,
59
+ "vf_coef": 0.5,
60
+ "max_grad_norm": 0.5,
61
+ "batch_size": 64,
62
+ "n_epochs": 4,
63
+ "clip_range": {
64
+ ":type:": "<class 'function'>",
65
+ ":serialized:": "gAWVxgEAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUtDQwRkAVMAlE5HAAAAAAAAAACGlCmMAV+UhZSMHzxpcHl0aG9uLWlucHV0LTY0LWEwMzk5MGNjNzNlNj6UjAg8bGFtYmRhPpRLDEMCBACUKSl0lFKUfZQojAtfX3BhY2thZ2VfX5ROjAhfX25hbWVfX5SMCF9fbWFpbl9flHVOTk50lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaBZ9lH2UKGgTaA2MDF9fcXVhbG5hbWVfX5RoDYwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoFIwHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5ROjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
66
+ },
67
+ "clip_range_vf": null,
68
+ "normalize_advantage": true,
69
+ "target_kl": null,
70
  "observation_space": {
71
  ":type:": "<class 'gymnasium.spaces.box.Box'>",
72
+ ":serialized:": "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",
73
  "dtype": "float32",
74
  "bounded_below": "[ True True True True True True True True]",
75
  "bounded_above": "[ True True True True True True True True]",
 
84
  },
85
  "action_space": {
86
  ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
87
+ ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
88
  "n": "4",
89
  "start": "0",
90
  "_shape": [],
 
92
  "_np_random": null
93
  },
94
  "n_envs": 16,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
95
  "lr_schedule": {
96
  ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
  }
99
  }
ppo-LunarLander-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f6b1994161ae4bba2374dd3c9e6ba0658daa211701b4ea68a921f01ae18f6538
3
- size 87929
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9df9c7dc9b022c32d359f889fdd95f0be5079c6f73466d2d67b5f1e81dac467f
3
+ size 88490
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:fd26f6f8205145b2a92d10f1f5ccc88a49f091b58e2b4fbf011418539b322be6
3
- size 43329
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1e3a9c539677b3e1719bd2ac25affdbd42898aaf06c5c1aef974a8ea0a4566c1
3
+ size 43762
ppo-LunarLander-v2/pytorch_variables.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
- size 431
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt CHANGED
@@ -1,9 +1,9 @@
1
- - OS: Linux-5.15.133+-x86_64-with-glibc2.35 # 1 SMP Wed Nov 8 17:30:28 UTC 2023
2
  - Python: 3.10.12
3
  - Stable-Baselines3: 2.0.0a5
4
- - PyTorch: 2.0.0
5
  - GPU Enabled: True
6
- - Numpy: 1.24.3
7
- - Cloudpickle: 3.0.0
8
- - Gymnasium: 0.28.1
9
- - OpenAI Gym: 0.26.2
 
1
+ - OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
2
  - Python: 3.10.12
3
  - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu118
5
  - GPU Enabled: True
6
+ - Numpy: 1.23.5
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.29.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (178 kB). View file
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 259.7422869, "std_reward": 23.11465620484487, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-25T12:47:22.761167"}
 
1
+ {"mean_reward": 265.8982623, "std_reward": 17.534898935633493, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-26T09:52:12.026863"}