double batch, epochs, steps, timesteps
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2-002.zip +3 -0
- ppo-LunarLander-v2-002/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2-002/data +99 -0
- ppo-LunarLander-v2-002/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2-002/policy.pth +3 -0
- ppo-LunarLander-v2-002/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2-002/system_info.txt +9 -0
- replay.mp4 +0 -0
- 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: 290.00 +/- 15.59
|
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 0x7efb606970a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb60697130>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb606971c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb60697250>", "_build": "<function ActorCriticPolicy._build at 0x7efb606972e0>", "forward": "<function ActorCriticPolicy.forward at 0x7efb60697370>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efb60697400>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb60697490>", "_predict": "<function ActorCriticPolicy._predict at 0x7efb60697520>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb606975b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb60697640>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb606976d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efb6b39c600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688248078678643801, "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:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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 0x7efb606970a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb60697130>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb606971c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb60697250>", "_build": "<function ActorCriticPolicy._build at 0x7efb606972e0>", "forward": "<function ActorCriticPolicy.forward at 0x7efb60697370>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efb60697400>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb60697490>", "_predict": "<function ActorCriticPolicy._predict at 0x7efb60697520>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb606975b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb60697640>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb606976d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efb6b39c600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688249441430229487, "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": 744, "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:": "gAWVgQEAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlIwUbnVtcHkucmFuZG9tLl9waWNrbGWUjBBfX2dlbmVyYXRvcl9jdG9ylJOUjAVQQ0c2NJSFlFKUfZQojA1iaXRfZ2VuZXJhdG9ylIwFUENHNjSUjAVzdGF0ZZR9lChoI4oQxooOv9KFaGO8Q16rFSu/AIwDaW5jlIoRz/cMvwhmIdXh4C5XXXeh0gB1jApoYXNfdWludDMylEsAjAh1aW50ZWdlcpRKx67XY3VidWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2-002.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e7bdd144be6734ec475f38d37f067b55aed988d318b935da54724a1439bc3c2d
|
3 |
+
size 146866
|
ppo-LunarLander-v2-002/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2-002/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 0x7efb606970a0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb60697130>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb606971c0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb60697250>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7efb606972e0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7efb60697370>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7efb60697400>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb60697490>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7efb60697520>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb606975b0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb60697640>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb606976d0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7efb6b39c600>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 2031616,
|
25 |
+
"_total_timesteps": 2000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1688249441430229487,
|
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": -0.015808000000000044,
|
45 |
+
"_stats_window_size": 100,
|
46 |
+
"ep_info_buffer": {
|
47 |
+
":type:": "<class 'collections.deque'>",
|
48 |
+
":serialized:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHLiFghKUV2MAWyUS7CMAXSUR0C6NfxxHXmOdX2UKGgGR0Bzm6X8fmtAaAdLwGgIR0C6Ng0y1uzhdX2UKGgGR0Byx/dAPd2xaAdLt2gIR0C6NkBCUorndX2UKGgGR0BzHb69CeEqaAdLy2gIR0C6NlsTrVvudX2UKGgGR0B0LJA7gbZOaAdL12gIR0C6NlyDZlFudX2UKGgGR0ByRD1bqyGBaAdLomgIR0C6NoN7SiM6dX2UKGgGR0BwxkDs+mm+aAdLwmgIR0C6NonUMG5ddX2UKGgGR0BvpmaDwpfAaAdLrWgIR0C6Nryzw+dLdX2UKGgGR0Bx0fsNUfgaaAdLl2gIR0C6Ns8LF4s3dX2UKGgGR0BzGTGlyimEaAdLs2gIR0C6NtMglnh9dX2UKGgGR0ByGIJeE7GOaAdLkWgIR0C6NtLyH2ytdX2UKGgGR0BzH5kZrHlwaAdLyGgIR0C6Nu5nUUfxdX2UKGgGR0BwMYEyLyc1aAdLqGgIR0C6NvoZydWidX2UKGgGR0Bw/fYpUgjhaAdLsGgIR0C6NxtFz+3pdX2UKGgGR0BymSJl8PWhaAdLzGgIR0C6Ny1d1MdtdX2UKGgGR0BwiHsjVx0daAdLuWgIR0C6N1Bx95QhdX2UKGgGR0BxY8t/WlMzaAdLrmgIR0C6N1LZBcAzdX2UKGgGR0Bxfbl7tzCDaAdLu2gIR0C6N1fTw2ETdX2UKGgGR0Bx6EiPhhphaAdLvmgIR0C6N685sCT2dX2UKGgGR0Bxk2cOLBKuaAdLvmgIR0C6N82kzoECdX2UKGgGR0BwyTTCtRvWaAdLrGgIR0C6N9/cSGrTdX2UKGgGR0BCubfYSQHSaAdLXWgIR0C6N+oQz1sddX2UKGgGR0B0XEnjQzDXaAdLt2gIR0C6N+9b9qDcdX2UKGgGR0BzCcVDa4+baAdL3GgIR0C6OAvWxyGSdX2UKGgGR0BxeH5O8CgcaAdLtWgIR0C6OCeaz/p/dX2UKGgGR0BxpF8ohIOIaAdLsmgIR0C6ODYJu2qldX2UKGgGR0By1pGOMl1KaAdLuWgIR0C6OEOaWom5dX2UKGgGR0ByRXWpZOi4aAdLrmgIR0C6OEiQgcLjdX2UKGgGR0Byk+2gFotdaAdLxmgIR0C6OFmWIGhVdX2UKGgGR0BwC163RXwLaAdLs2gIR0C6OF0Y0l7ddX2UKGgGR0By1kH9m6GyaAdLsmgIR0C6OHxcE/0NdX2UKGgGR0A3lXJ5mh/RaAdLWWgIR0C6OIyTpxFRdX2UKGgGR0Bx5/FKkEcLaAdLoWgIR0C6OJe+/QBxdX2UKGgGR0By9DG1hLGraAdLpWgIR0C6OJi9h7VsdX2UKGgGR0ByUAw/PgNxaAdLp2gIR0C6OJ6SDAaedX2UKGgGR0Bx2eRaHKwIaAdLnGgIR0C6OP3V9Wp7dX2UKGgGR0ByFf336AOKaAdLkWgIR0C6OQhmkFfRdX2UKGgGR0Bxn+6pYLb6aAdLvmgIR0C6OSfFJg9edX2UKGgGR0BvlJeRgZ0kaAdLsWgIR0C6OUBvm5lOdX2UKGgGR0BwsO6jFhoeaAdLo2gIR0C6OUNDlYEGdX2UKGgGR0Bw169PDYRNaAdLomgIR0C6OWVwxWT5dX2UKGgGR0BxcZyksSTRaAdLrGgIR0C6OWng9/z8dX2UKGgGR0BynKUA1ejVaAdLvmgIR0C6OXgcDKYBdX2UKGgGR0BxtC6XjU/faAdLtmgIR0C6OYLgbZOBdX2UKGgGR0Bw02LGaQV9aAdLnWgIR0C6OZi0rsjWdX2UKGgGR0BzFexLTQVsaAdLqmgIR0C6OZV8stkGdX2UKGgGR0BxaxrylN1yaAdLxGgIR0C6OaB+KCQLdX2UKGgGR0By/PVz6rNoaAdL1mgIR0C6ObeuaF23dX2UKGgGR0BwuVDUmUnpaAdLxGgIR0C6Ob+8brC4dX2UKGgGR0ByKA/MW43FaAdLymgIR0C6Oc8otthvdX2UKGgGR0BxasmICU5daAdL0mgIR0C6OdzIzWPMdX2UKGgGR0BwaHfP5YYBaAdLr2gIR0C6Oe+cQRPHdX2UKGgGR0BwYfcM3IdVaAdLrGgIR0C6OfFMqSX/dX2UKGgGR0ByT97sv7FbaAdLmGgIR0C6OgA/keZHdX2UKGgGR0BzM0/s3Q2NaAdLumgIR0C6OhisGPgfdX2UKGgGR0BzUQ482aUiaAdLtWgIR0C6OiUvXbuddX2UKGgGR0BwMwe1a4c4aAdLnWgIR0C6Oj4z7/GVdX2UKGgGR0ByH6lHjIaMaAdLx2gIR0C6OmJx//eddX2UKGgGR0Bzl+3uuzQeaAdLvmgIR0C6OnU3bVSXdX2UKGgGR0ByFfWMCLdfaAdLlmgIR0C6Onk+PikwdX2UKGgGR0Bzj0nRb8m8aAdL2WgIR0C6On5xNqQBdX2UKGgGR0BxttNvfj0daAdLv2gIR0C6Oo2OdXkpdX2UKGgGR0ByoUavRqoIaAdLv2gIR0C6OpUZrHlwdX2UKGgGR0ByMkQd0aIfaAdLx2gIR0C6OpR1LamGdX2UKGgGR0BxU8IC2c8UaAdLtGgIR0C6OqbYf4h2dX2UKGgGR0BxllrBTGYKaAdLtmgIR0C6OsSq2jO+dX2UKGgGR0ByV3QkX1rZaAdLrWgIR0C6Osy1/lQudX2UKGgGR0ByrRTjvNNbaAdLzGgIR0C6OtOlj3EidX2UKGgGR0BvtFbC79Q5aAdLtWgIR0C6OtpeiSJTdX2UKGgGR0ByqfF85S3taAdLy2gIR0C6OwZuqFRHdX2UKGgGR0BxOmjfvWpZaAdLq2gIR0C6OxpGrjo7dX2UKGgGR0BzIyMvRJEqaAdLw2gIR0C6OyAlnh86dX2UKGgGR0Bzkn1Iy0rtaAdL/mgIR0C6O2Edq+JxdX2UKGgGR0Bvl6BGx2SuaAdLv2gIR0C6O2wT238XdX2UKGgGR0BwPCf8MuvmaAdLnmgIR0C6O3Y2Kl54dX2UKGgGR0Bx9gzuWrwOaAdL2GgIR0C6O3wE6kqMdX2UKGgGR0ByOu0v4/NaaAdLzWgIR0C6O4TCtRvWdX2UKGgGR0BxhF0OmR/3aAdLumgIR0C6O4eY+jdpdX2UKGgGR0Byb1mwqy4XaAdLxWgIR0C6O41ruYx+dX2UKGgGR0ByAaGj9GZvaAdLv2gIR0C6O4w04zacdX2UKGgGR0Byo5r2xptaaAdL0mgIR0C6O46ya/h3dX2UKGgGR0Bwy5vfj0cwaAdLr2gIR0C6O7XTEzfrdX2UKGgGR0Bz9XI7vG6xaAdLtWgIR0C6O8KlUIcBdX2UKGgGR0ByBh4u9OARaAdLzmgIR0C6O8/0mMOxdX2UKGgGR0ByPrC3w1BMaAdL02gIR0C6O96EOAiFdX2UKGgGR0BxNuMNtqHoaAdLtWgIR0C6O+9o371qdX2UKGgGR0Bx12ZtvXK9aAdLsmgIR0C6PANVJcxCdX2UKGgGR0BzuXQOWjXWaAdL2mgIR0C6PDW12JSBdX2UKGgGR0BxI+ZRbbDeaAdLmWgIR0C6PEvNzKcNdX2UKGgGR0BwJS+PBBRiaAdLrGgIR0C6PFvAoG6gdX2UKGgGR0ByXYOnVG1AaAdLqWgIR0C6PGBVZLZjdX2UKGgGR0BvJW1v2oNvaAdLxmgIR0C6PGWIwdsBdX2UKGgGR0By9ru2JBPbaAdLwmgIR0C6PGseGO+7dX2UKGgGR0Bwu9S4vvjPaAdLsmgIR0C6PHWbobGWdX2UKGgGR0BzGkf7rLQpaAdL1mgIR0C6PIsi0OVgdX2UKGgGR0BxBnvJA+pwaAdLm2gIR0C6PJEnLJS0dX2UKGgGR0Byo4b+98JEaAdLp2gIR0C6PJOFHrhSdX2UKGgGR0ByqvqFAVwhaAdLy2gIR0C6PJLDAJswdX2UKGgGR0BzCC49X9zfaAdL1mgIR0C6PKE1Q66rdX2UKGgGR0BxSq0b961LaAdLpWgIR0C6PKdtQ9A5dWUu"
|
49 |
+
},
|
50 |
+
"ep_success_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
+
},
|
54 |
+
"_n_updates": 744,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "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",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "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",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": "Generator(PCG64)"
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
80 |
+
"n_steps": 2048,
|
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": 128,
|
87 |
+
"n_epochs": 8,
|
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-v2-002/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:80fc0a08675f9040749299e412d2b5a9da1c3a8ab093e43185dfe0a09e411dd8
|
3 |
+
size 87929
|
ppo-LunarLander-v2-002/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1cb05f9ab047188cbc119d2ba935b6330abaf1db9bf776197b5e8743a9bf94cd
|
3 |
+
size 43329
|
ppo-LunarLander-v2-002/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
ppo-LunarLander-v2-002/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.0.1+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 289.9984216, "std_reward": 15.591066492953983, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-01T22:38:52.359831"}
|