DNA-55 commited on
Commit
3c2edbe
1 Parent(s): ff407dc

Upload a sample of PPO LunarLander-v2 trained agent with TS=100000

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 264.22 +/- 18.46
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 267.92 +/- 10.56
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 0x799f1dae2710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x799f1dae27a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x799f1dae2830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x799f1dae28c0>", "_build": "<function ActorCriticPolicy._build at 0x799f1dae2950>", "forward": "<function ActorCriticPolicy.forward at 0x799f1dae29e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x799f1dae2a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x799f1dae2b00>", "_predict": "<function ActorCriticPolicy._predict at 0x799f1dae2b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x799f1dae2c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x799f1dae2cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x799f1dae2d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x799f1dad96c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 131072, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713257838524409061, "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": -0.3107200000000001, "_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": 270, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "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-6.1.58+-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": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
 
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 0x7d11cce10b80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d11cce10c10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d11cce10ca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d11cce10d30>", "_build": "<function ActorCriticPolicy._build at 0x7d11cce10dc0>", "forward": "<function ActorCriticPolicy.forward at 0x7d11cce10e50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d11cce10ee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d11cce10f70>", "_predict": "<function ActorCriticPolicy._predict at 0x7d11cce11000>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d11cce11090>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d11cce11120>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d11cce111b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d11ccfadc40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713268240893268784, "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": 496, "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": 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": 8, "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": "2.2.1+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "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 sha256:64a6f0313e46306ec2ecca00bc0df94c2fddeda71939da260bc2ff84bef71ba0
3
- size 147975
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e5a8ae9ddf93a548e9c2ed4cd83477efa0148175ed3cfc88011f815eee649fb9
3
+ size 147517
ppo-LunarLander-v2/data CHANGED
@@ -4,34 +4,34 @@
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 0x799f1dae2710>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x799f1dae27a0>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x799f1dae2830>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x799f1dae28c0>",
11
- "_build": "<function ActorCriticPolicy._build at 0x799f1dae2950>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x799f1dae29e0>",
13
- "extract_features": "<function ActorCriticPolicy.extract_features at 0x799f1dae2a70>",
14
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x799f1dae2b00>",
15
- "_predict": "<function ActorCriticPolicy._predict at 0x799f1dae2b90>",
16
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x799f1dae2c20>",
17
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x799f1dae2cb0>",
18
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x799f1dae2d40>",
19
  "__abstractmethods__": "frozenset()",
20
- "_abc_impl": "<_abc._abc_data object at 0x799f1dad96c0>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
24
- "num_timesteps": 131072,
25
- "_total_timesteps": 100000,
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
- "start_time": 1713257838524409061,
30
  "learning_rate": 0.0003,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
34
- ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAICWnb3Lv4A+9fYVPr8F9L5URfc7hq/sPAAAAAAAAAAAc+SBve/dGz8DCuS8QEn/vgCl+byKtzo9AAAAAAAAAADz5co9ezKMumWl57n89jM0c9g8u1+HAzkAAIA/AACAP7pnvb4RwDo/fzDAvNmhAb820aW+IH3BPAAAAAAAAAAAs8iPva4Bl7puH6e21/KosRxui7qlzsU1AACAPwAAgD8z0hE+n+y6u5IYMzxts4C6JHIdvfWtWbsAAIA/AACAPyrloD46WOY+/1miPQ2nGr9yuLQ+uSGsvQAAAAAAAAAAWsERvmzh37tgAQG7YvY0uY/tLj0zqBg6AACAPwAAgD8AGB48VIa0P1rUJT63JI+9BH9Su4uAU7wAAAAAAAAAAKCINj5bpIu8AYsKPHaHfLqe0PK91BVJuwAAgD8AAIA/zdwFvs6vqD8S3iO/DKrcvgYa470nxJu+AAAAAAAAAAD61mK+D1luPx5Wq753Y+y+FKSrvhOU+70AAAAAAAAAAJOECL5mvbs/2nAAv9S/dL76W62935fEvQAAAAAAAAAAM9r0vOKBuT8VGR++m1MbvhnbnLxE08K8AAAAAAAAAADa7QI+uIyGu6pxSz1c3La7uP3fvJ0vnLwAAAAAAACAPzPd97xkVt0+sS81PU7A1r7pVbS8szhVPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
35
  },
36
  "_last_episode_starts": {
37
  ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
41
  "_episode_num": 0,
42
  "use_sde": false,
43
  "sde_sample_freq": -1,
44
- "_current_progress_remaining": -0.3107200000000001,
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": 270,
55
  "observation_space": {
56
  ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
  ":serialized:": "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",
@@ -77,14 +77,14 @@
77
  "_np_random": null
78
  },
79
  "n_envs": 16,
80
- "n_steps": 2048,
81
- "gamma": 0.99,
82
- "gae_lambda": 0.95,
83
- "ent_coef": 0.0,
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:": "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"
 
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 0x7d11cce10b80>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d11cce10c10>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d11cce10ca0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d11cce10d30>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7d11cce10dc0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7d11cce10e50>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d11cce10ee0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d11cce10f70>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7d11cce11000>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d11cce11090>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d11cce11120>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d11cce111b0>",
19
  "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7d11ccfadc40>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
+ "start_time": 1713268240893268784,
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'>",
 
41
  "_episode_num": 0,
42
  "use_sde": false,
43
  "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.015808000000000044,
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": 496,
55
  "observation_space": {
56
  ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
  ":serialized:": "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",
 
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": 8,
88
  "clip_range": {
89
  ":type:": "<class 'function'>",
90
  ":serialized:": "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"
ppo-LunarLander-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5805e4c0d7e89d235dec0734cc6287a3e93828987035e81a18ae46f1523fd906
3
- size 88362
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:80ffc79b9c8d3488ce94c0ca56a471310a09cf62f647f3522f2e04c3639a4451
3
+ size 87978
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9b6f9ce04854e24145ae965e130af55075b32e42567a92bef9a75623b9337490
3
- size 43762
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:664426b0b544284e08c8542ba64189126f1caa4bdb9c0648011cef45c0da74aa
3
+ size 43634
ppo-LunarLander-v2/system_info.txt CHANGED
@@ -2,7 +2,7 @@
2
  - Python: 3.10.12
3
  - Stable-Baselines3: 2.0.0a5
4
  - PyTorch: 2.2.1+cu121
5
- - GPU Enabled: True
6
  - Numpy: 1.25.2
7
  - Cloudpickle: 2.2.1
8
  - Gymnasium: 0.28.1
 
2
  - Python: 3.10.12
3
  - Stable-Baselines3: 2.0.0a5
4
  - PyTorch: 2.2.1+cu121
5
+ - GPU Enabled: False
6
  - Numpy: 1.25.2
7
  - Cloudpickle: 2.2.1
8
  - Gymnasium: 0.28.1
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 264.21879049999995, "std_reward": 18.46319953455132, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-16T09:23:00.645180"}
 
1
+ {"mean_reward": 267.9158218, "std_reward": 10.559295210980315, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-16T12:21:23.743887"}