Upload PPO LunarLANDER trained model
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2-3.zip +3 -0
- ppo-LunarLander-v2-3/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2-3/data +99 -0
- ppo-LunarLander-v2-3/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2-3/policy.pth +3 -0
- ppo-LunarLander-v2-3/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2-3/system_info.txt +9 -0
- replay.mp4 +2 -2
- results.json +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value:
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: 272.06 +/- 22.66
|
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 0x78d45a46ede0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78d45a46ee80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78d45a46ef20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78d45a46efc0>", "_build": "<function ActorCriticPolicy._build at 0x78d45a46f060>", "forward": "<function ActorCriticPolicy.forward at 0x78d45a46f100>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78d45a46f1a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78d45a46f240>", "_predict": "<function ActorCriticPolicy._predict at 0x78d45a46f2e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78d45a46f380>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78d45a46f420>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78d45a46f4c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78d45a5e2980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742228693949370117, "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": 310, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "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 0x7935aab38ea0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7935aab38f40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7935aab38fe0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7935aab39080>", "_build": "<function ActorCriticPolicy._build at 0x7935aab39120>", "forward": "<function ActorCriticPolicy.forward at 0x7935aab391c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7935aab39260>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7935aab39300>", "_predict": "<function ActorCriticPolicy._predict at 0x7935aab393a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7935aab39440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7935aab394e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7935aab39580>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7935aacab9c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1007616, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1744214389751995727, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAACAA4m9FHyOutearruAsu0xynyaunuZ/bMAAIA/AACAP80W/Dwd9Ws/H8k3PfW25r5bNXI9syFavQAAAAAAAAAAwDjhvS6h+T3Ypzw9+qhlvi+7jbwYLa28AAAAAAAAAABaWzw+sZWPPw39tz7JUwW/NgFvPjTcybwAAAAAAAAAAM2/Nb53/kI/szUwvgpMsb5AABy+bwhCPQAAAAAAAAAAzVibvTSd0j16EMW9kMNsvgs2IL3j8ls9AAAAAAAAAAAzXgM9KXx8usb84zqzS5Q1bcgPuzRLBboAAIA/AACAP43cLL4Rxf8966R7PZaPab5G0PC7yrvOPAAAAAAAAAAAY9llvhgdjj74bpI9rclgvoxI9Ly/OMo8AAAAAAAAAAAAX0S9e9iXujyAKbx1b184HScPu2a2yLcAAIA/AACAP5ozqjz2KD66pDsVOt6InjW374U7KhgtuQAAgD8AAIA/8L6EPpt0Jz+UxqS9lUbmvhCXIz5Hd4S9AAAAAAAAAAAG7yI+WLohPz6KDLxlure+1DjpPVYG5rwAAAAAAAAAALN/Cz7ss/C7dtHSupR90TgMI0m9P8cOOgAAgD8AAIA/ADTgPKmgJrwWi0K+V/mZvO34oTwoA3w+AACAPwAAgD9N2IW9YSRqPlf5mL0tFFi+rMgUO6DRxjsAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.007616000000000067, "_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": 1230, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 512, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "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": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2-3.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2d700dfcbf3778baca4ce7ed766352424219d5ba59398f567b16b7ce2d839864
|
3 |
+
size 148042
|
ppo-LunarLander-v2-3/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2-3/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 0x7935aab38ea0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7935aab38f40>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7935aab38fe0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7935aab39080>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7935aab39120>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7935aab391c0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7935aab39260>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7935aab39300>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7935aab393a0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7935aab39440>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7935aab394e0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7935aab39580>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7935aacab9c0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1007616,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1744214389751995727,
|
30 |
+
"learning_rate": 0.001,
|
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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -0.007616000000000067,
|
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": 1230,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "gAWVdwIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZROdWIu",
|
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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
80 |
+
"n_steps": 512,
|
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": 128,
|
87 |
+
"n_epochs": 10,
|
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-v2-3/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:784b7d8e6979f881c17f7d142078d9d83d859ad289a12458a2facd86aaf2a477
|
3 |
+
size 88362
|
ppo-LunarLander-v2-3/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6b570a644bc824f48c40c8a96403083f0e07c06b53e2274afd2f6d763a801255
|
3 |
+
size 43762
|
ppo-LunarLander-v2-3/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-v2-3/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: 3.11.11
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.6.0+cu124
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 2.0.2
|
7 |
+
- Cloudpickle: 3.1.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1ec5905ca153ef055d411cf21df72b976bf313efcefecfef1737470694567a81
|
3 |
+
size 150533
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 272.0624126999999, "std_reward": 22.659462162319443, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-04-09T16:27:12.060820"}
|