Upload PPO LunarLander-v2 trained agent
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +99 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/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: 220.43 +/- 49.61
|
| 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 0x7fcaac9d3760>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcaac9d37f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcaac9d3880>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcaac9d3910>", "_build": "<function ActorCriticPolicy._build at 0x7fcaac9d39a0>", "forward": "<function ActorCriticPolicy.forward at 0x7fcaac9d3a30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fcaac9d3ac0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcaac9d3b50>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcaac9d3be0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcaac9d3c70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcaac9d3d00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcaac9d3d90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fcaac9e0540>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1707342902474290191, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAACY32L2+Yps/q6ubvkWtxL76QAS+CBkevQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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": "Generator(PCG64)"}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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-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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "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 0x7a98c7049bd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a98c7049c60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a98c7049cf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a98c7049d80>", "_build": "<function ActorCriticPolicy._build at 0x7a98c7049e10>", "forward": "<function ActorCriticPolicy.forward at 0x7a98c7049ea0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a98c7049f30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a98c7049fc0>", "_predict": "<function ActorCriticPolicy._predict at 0x7a98c704a050>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a98c704a0e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a98c704a170>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a98c704a200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a98c6fe7bc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1048576, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1707745263444874786, "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:": "gAWVswAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiS0CFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.04857599999999995, "_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": 72, "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": 64, "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-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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8bff1c4b59a7487351571a7e1f04b3aa2fe2804a6be3b8ac05835c9ff61ed171
|
| 3 |
+
size 150174
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
2.0.0a5
|
ppo-LunarLander-v2/data
ADDED
|
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"policy_class": {
|
| 3 |
+
":type:": "<class 'abc.ABCMeta'>",
|
| 4 |
+
":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
|
| 5 |
+
"__module__": "stable_baselines3.common.policies",
|
| 6 |
+
"__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ",
|
| 7 |
+
"__init__": "<function ActorCriticPolicy.__init__ at 0x7a98c7049bd0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a98c7049c60>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a98c7049cf0>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a98c7049d80>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7a98c7049e10>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7a98c7049ea0>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7a98c7049f30>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a98c7049fc0>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7a98c704a050>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a98c704a0e0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a98c704a170>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7a98c704a200>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7a98c6fe7bc0>"
|
| 21 |
+
},
|
| 22 |
+
"verbose": 1,
|
| 23 |
+
"policy_kwargs": {},
|
| 24 |
+
"num_timesteps": 1048576,
|
| 25 |
+
"_total_timesteps": 1000000,
|
| 26 |
+
"_num_timesteps_at_start": 0,
|
| 27 |
+
"seed": null,
|
| 28 |
+
"action_noise": null,
|
| 29 |
+
"start_time": 1707745263444874786,
|
| 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:": "gAWVswAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiS0CFlIwBQ5R0lFKULg=="
|
| 39 |
+
},
|
| 40 |
+
"_last_original_obs": null,
|
| 41 |
+
"_episode_num": 0,
|
| 42 |
+
"use_sde": false,
|
| 43 |
+
"sde_sample_freq": -1,
|
| 44 |
+
"_current_progress_remaining": -0.04857599999999995,
|
| 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": 72,
|
| 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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
| 73 |
+
"n": "4",
|
| 74 |
+
"start": "0",
|
| 75 |
+
"_shape": [],
|
| 76 |
+
"dtype": "int64",
|
| 77 |
+
"_np_random": null
|
| 78 |
+
},
|
| 79 |
+
"n_envs": 64,
|
| 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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
| 98 |
+
}
|
| 99 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c313e59b01e0f29ab9c76d19585188043e70fb2a6f30bc72a76ae96fd435ed75
|
| 3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ce432b3dd50951bb73a3fe27b57c19cfa81ac0eb5e84a99f541c8c17adebf0e4
|
| 3 |
+
size 43762
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
| 3 |
+
size 864
|
ppo-LunarLander-v2/system_info.txt
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
|
| 2 |
+
- Python: 3.10.12
|
| 3 |
+
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.1.0+cu121
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 1.23.5
|
| 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": 220.43107276228756, "std_reward": 49.60618654289128, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-12T14:06:15.166792"}
|