Goddrew commited on
Commit
edc58ea
1 Parent(s): 8782bc4

upload ppo LunarLander-v2 agent

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 259.61 +/- 17.91
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +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 0x7fbc12cb6dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbc12cb6e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbc12cb6ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbc12cb6f70>", "_build": "<function ActorCriticPolicy._build at 0x7fbc12cb9040>", "forward": "<function ActorCriticPolicy.forward at 0x7fbc12cb90d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fbc12cb9160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbc12cb91f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbc12cb9280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbc12cb9310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbc12cb93a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbc12cb9430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fbc12cb44b0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676421490007695190, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:316cc811506446b727066c8833c50cea0eab32ac91c0f1cfb37b1730dc2b22f1
3
+ size 147420
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7fbc12cb6dc0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbc12cb6e50>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbc12cb6ee0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbc12cb6f70>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fbc12cb9040>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fbc12cb90d0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fbc12cb9160>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbc12cb91f0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fbc12cb9280>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbc12cb9310>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbc12cb93a0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbc12cb9430>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7fbc12cb44b0>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "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",
27
+ "dtype": "float32",
28
+ "_shape": [
29
+ 8
30
+ ],
31
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
32
+ "high": "[inf inf inf inf inf inf inf inf]",
33
+ "bounded_below": "[False False False False False False False False]",
34
+ "bounded_above": "[False False False False False False False False]",
35
+ "_np_random": null
36
+ },
37
+ "action_space": {
38
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
39
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
40
+ "n": 4,
41
+ "_shape": [],
42
+ "dtype": "int64",
43
+ "_np_random": null
44
+ },
45
+ "n_envs": 16,
46
+ "num_timesteps": 1015808,
47
+ "_total_timesteps": 1000000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1676421490007695190,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
57
+ },
58
+ "_last_obs": {
59
+ ":type:": "<class 'numpy.ndarray'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "_last_episode_starts": {
63
+ ":type:": "<class 'numpy.ndarray'>",
64
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
65
+ },
66
+ "_last_original_obs": null,
67
+ "_episode_num": 0,
68
+ "use_sde": false,
69
+ "sde_sample_freq": -1,
70
+ "_current_progress_remaining": -0.015808000000000044,
71
+ "ep_info_buffer": {
72
+ ":type:": "<class 'collections.deque'>",
73
+ ":serialized:": "gAWVfRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI5pSAmISMW0CUhpRSlIwBbJRN6AOMAXSUR0CZkjwpvxYrdX2UKGgGaAloD0MIu/HuyFgtbUCUhpRSlGgVTUYBaBZHQJmTeJAMUh51fZQoaAZoCWgPQwiqZtZSQAFwQJSGlFKUaBVNhwFoFkdAmZVtALRa5nV9lChoBmgJaA9DCNsUj4uqTnFAlIaUUpRoFU1HAWgWR0CZsRMefZmJdX2UKGgGaAloD0MIRmEXRc/jcECUhpRSlGgVTZQBaBZHQJmxIUnG8291fZQoaAZoCWgPQwhVF/AyQy5rQJSGlFKUaBVNZwFoFkdAmbKR/ViF03V9lChoBmgJaA9DCJw0DYrmwm5AlIaUUpRoFU1RAWgWR0CZsp4tYjjadX2UKGgGaAloD0MIFHZR9MB3cUCUhpRSlGgVTTYBaBZHQJm0Oe6I3zd1fZQoaAZoCWgPQwip3hrYqq5yQJSGlFKUaBVNcAFoFkdAmbR9pM6BAnV9lChoBmgJaA9DCAltOZfimHBAlIaUUpRoFU2tAWgWR0CZthi9IwuedX2UKGgGaAloD0MI2nOZmoQJckCUhpRSlGgVTWIBaBZHQJm2JQ2uPmx1fZQoaAZoCWgPQwhzKhkAKghwQJSGlFKUaBVNIgFoFkdAmbZUUj9n9XV9lChoBmgJaA9DCBGo/kGkKnJAlIaUUpRoFU1zAWgWR0CZt2J40Mw2dX2UKGgGaAloD0MIF4BG6RKYcECUhpRSlGgVTZkBaBZHQJm3gnqmj0t1fZQoaAZoCWgPQwgTfxR15kJrQJSGlFKUaBVNOgFoFkdAmbgXi704BHV9lChoBmgJaA9DCG8u/rYnhG5AlIaUUpRoFU1oAWgWR0CZuPdGy5ZsdX2UKGgGaAloD0MICvSJPAmocUCUhpRSlGgVTRABaBZHQJm6GkCV8kV1fZQoaAZoCWgPQwjuX1lp0jFwQJSGlFKUaBVNcQFoFkdAmbp6e05U+HV9lChoBmgJaA9DCAdF8wCWmnBAlIaUUpRoFU1xAWgWR0CZu6tNBWxRdX2UKGgGaAloD0MIgh5q2/B+ckCUhpRSlGgVTTQBaBZHQJm8pLPD50t1fZQoaAZoCWgPQwjHuriNho9uQJSGlFKUaBVNRQFoFkdAmb7D94u9OHV9lChoBmgJaA9DCGe2K/QBB3FAlIaUUpRoFU1uAWgWR0CZwHoL5RCQdX2UKGgGaAloD0MIdeYeEv6TcECUhpRSlGgVTaEBaBZHQJnBHiMo+fR1fZQoaAZoCWgPQwjgKk8grO5wQJSGlFKUaBVNUwFoFkdAmcF6Xv6TGHV9lChoBmgJaA9DCHGPpQ+dVXJAlIaUUpRoFU05AWgWR0CZwoIX0oSddX2UKGgGaAloD0MIMGR1q2eacECUhpRSlGgVTWcBaBZHQJnFKDaoMrp1fZQoaAZoCWgPQwjf/fFe9aFwQJSGlFKUaBVNRgFoFkdAmcVTc6/7BXV9lChoBmgJaA9DCCdqaW7FD3FAlIaUUpRoFU10AWgWR0CZxevx6OYIdX2UKGgGaAloD0MINzl80kllcUCUhpRSlGgVTXcBaBZHQJnH562OQyR1fZQoaAZoCWgPQwgL0oxF01RvQJSGlFKUaBVNaAFoFkdAmcg1XiiqQ3V9lChoBmgJaA9DCG8QrRVtbG9AlIaUUpRoFU3RAWgWR0CZyIsAvL5idX2UKGgGaAloD0MIqWvtfWobcUCUhpRSlGgVTVkBaBZHQJnIuj/Mnqp1fZQoaAZoCWgPQwgP8Q9bephJQJSGlFKUaBVL+mgWR0CZyUIKc/dJdX2UKGgGaAloD0MIF9f4TLafckCUhpRSlGgVTUgBaBZHQJnJkiml67d1fZQoaAZoCWgPQwh1HaopSWlvQJSGlFKUaBVNRAFoFkdAmctDN+so2HV9lChoBmgJaA9DCGgIxyx7BjJAlIaUUpRoFUvXaBZHQJnMfs0HhS91fZQoaAZoCWgPQwjSNv5EJSxwQJSGlFKUaBVNnAFoFkdAmc3X6VMVUXV9lChoBmgJaA9DCNukorH2Em9AlIaUUpRoFU1CAWgWR0CZzyiVSn+AdX2UKGgGaAloD0MIJ0ut99v/cECUhpRSlGgVTTsBaBZHQJnQ0/nnuAt1fZQoaAZoCWgPQwhSJjW0gS9sQJSGlFKUaBVNSgFoFkdAmdLGRFI/aHV9lChoBmgJaA9DCP+R6dBp8mxAlIaUUpRoFU0tAWgWR0CZ1OS+QEIPdX2UKGgGaAloD0MI58Qe2scrcECUhpRSlGgVTW0BaBZHQJnWhRiw0O51fZQoaAZoCWgPQwgYd4NobR1xQJSGlFKUaBVL/WgWR0CZ1y0mdAgQdX2UKGgGaAloD0MIiPVGrXA4cECUhpRSlGgVTTgBaBZHQJnZt8b70nR1fZQoaAZoCWgPQwjlYaHWtI9wQJSGlFKUaBVNIgFoFkdAmdnI/eLvTnV9lChoBmgJaA9DCK6cvTMaOnBAlIaUUpRoFU12AWgWR0CZ2eQA+6iCdX2UKGgGaAloD0MIWkqWkxAVcUCUhpRSlGgVTVkBaBZHQJnauTQmeDp1fZQoaAZoCWgPQwgLR5BKsSJwQJSGlFKUaBVNmQFoFkdAmdwnJtBOYnV9lChoBmgJaA9DCFvtYS8UQG9AlIaUUpRoFU1xAWgWR0CZ3EFdcB2fdX2UKGgGaAloD0MIiuWWVgM2cUCUhpRSlGgVTZoBaBZHQJnezxpcoph1fZQoaAZoCWgPQwh9zt2u16JwQJSGlFKUaBVNegFoFkdAmeBad+Xqq3V9lChoBmgJaA9DCBiYFYr09m9AlIaUUpRoFU1RAWgWR0CZ4PrTYukDdX2UKGgGaAloD0MIih74GKyycUCUhpRSlGgVTWEBaBZHQJn5lc7hegN1fZQoaAZoCWgPQwiaC1weKyRxQJSGlFKUaBVNqQFoFkdAmfo/Tw2ETXV9lChoBmgJaA9DCNqqJLJP3nBAlIaUUpRoFU03AWgWR0CZ+oEA5q/NdX2UKGgGaAloD0MIPpP983Q/ckCUhpRSlGgVTXsBaBZHQJn7xsP8Q7N1fZQoaAZoCWgPQwiYbhKDwJZwQJSGlFKUaBVNJAFoFkdAmf3mfbsWwnV9lChoBmgJaA9DCIfAkUCD8G1AlIaUUpRoFU1YAWgWR0CZ/f/UONHZdX2UKGgGaAloD0MIlnZqLvdqcECUhpRSlGgVTXEBaBZHQJn+H0z0pVl1fZQoaAZoCWgPQwjYYUz6e8hxQJSGlFKUaBVNLQFoFkdAmf5Ko2n89HV9lChoBmgJaA9DCP7w89+DxnBAlIaUUpRoFU1cAWgWR0CZ/mYbsF+vdX2UKGgGaAloD0MIPX/aqE5tcUCUhpRSlGgVTS0BaBZHQJn+9jOLR8d1fZQoaAZoCWgPQwgRqWkXU0JwQJSGlFKUaBVNNAFoFkdAmgBKzu4PPXV9lChoBmgJaA9DCBmO5zMgqW1AlIaUUpRoFU1jAWgWR0CaAGBGQSzxdX2UKGgGaAloD0MIvoi2Y2oPcUCUhpRSlGgVTUUBaBZHQJoCt/QSi/R1fZQoaAZoCWgPQwhFoPoHkdVtQJSGlFKUaBVNIAFoFkdAmgLKlYU343V9lChoBmgJaA9DCP8+48KBCm9AlIaUUpRoFU2OAWgWR0CaA2W3BpHqdX2UKGgGaAloD0MI9FDbhlEQbECUhpRSlGgVTWUBaBZHQJoEt8c+7lJ1fZQoaAZoCWgPQwhLrIxG/hxwQJSGlFKUaBVNSAFoFkdAmgWsxwhnrnV9lChoBmgJaA9DCN+j/npFanJAlIaUUpRoFU1NAWgWR0CaBtznzQNTdX2UKGgGaAloD0MIfLq6YzECb0CUhpRSlGgVTVkBaBZHQJoHEZ2pyZN1fZQoaAZoCWgPQwjkoISZNtdvQJSGlFKUaBVNIgFoFkdAmghujIq9XnV9lChoBmgJaA9DCDrpfeNrqnBAlIaUUpRoFU0ZAWgWR0CaCHq5byH3dX2UKGgGaAloD0MI2sngKDkMcUCUhpRSlGgVTTkBaBZHQJoJjns9jgB1fZQoaAZoCWgPQwiCdLFpJUlwQJSGlFKUaBVNOwFoFkdAmgnt74SHunV9lChoBmgJaA9DCKsINxkVDnBAlIaUUpRoFU15AWgWR0CaCe1y/9HddX2UKGgGaAloD0MIW18ktGVJcECUhpRSlGgVTWsBaBZHQJoMKTvAoG91fZQoaAZoCWgPQwiTGW8r/QxxQJSGlFKUaBVNWAFoFkdAmgzksSTQmnV9lChoBmgJaA9DCGrZWl+kSXBAlIaUUpRoFU1iAWgWR0CaDTE8JUo8dX2UKGgGaAloD0MIB5j5Dn4KcECUhpRSlGgVTTUBaBZHQJoOOpbUwzt1fZQoaAZoCWgPQwiFKF/QQpxwQJSGlFKUaBVN5gFoFkdAmg/7Qw9JSXV9lChoBmgJaA9DCB9lxAVgkXBAlIaUUpRoFU1wAWgWR0CaEbGvwEyMdX2UKGgGaAloD0MIXyaKkLolcECUhpRSlGgVTVUBaBZHQJoSYKiO/+N1fZQoaAZoCWgPQwiADB076BJxQJSGlFKUaBVNkQFoFkdAmhJvKdQO4HV9lChoBmgJaA9DCPyJyoY142tAlIaUUpRoFU0tAWgWR0CaE4I8QqZudX2UKGgGaAloD0MIYhQEj28jb0CUhpRSlGgVTRsBaBZHQJoWt7E5yU91fZQoaAZoCWgPQwiJfm39dA5xQJSGlFKUaBVNbgFoFkdAmhcCtA9mpXV9lChoBmgJaA9DCFhUxOnkl3FAlIaUUpRoFU1HAWgWR0CaFxIVM23sdX2UKGgGaAloD0MIV3kCYacIcECUhpRSlGgVTUgBaBZHQJoXLfxc3VF1fZQoaAZoCWgPQwi5NH7h1RhwQJSGlFKUaBVNxQFoFkdAmhorblA/s3V9lChoBmgJaA9DCHYYk/7ebnFAlIaUUpRoFU1mAWgWR0CaGlUqx1PndX2UKGgGaAloD0MI8mH2su3BbkCUhpRSlGgVTV8BaBZHQJoaezKLbYd1fZQoaAZoCWgPQwgArfnxl1BtQJSGlFKUaBVNLAFoFkdAmhxmgnMMZ3V9lChoBmgJaA9DCIPcRZhiAXBAlIaUUpRoFU09AWgWR0CaHN4YrJ8wdX2UKGgGaAloD0MI/9DMk2s3ckCUhpRSlGgVTU8BaBZHQJof6dkJ8fF1fZQoaAZoCWgPQwgZyol21elyQJSGlFKUaBVNGAFoFkdAmiH/W1+iJ3V9lChoBmgJaA9DCHC044bfI3BAlIaUUpRoFU0tAWgWR0CaIqbaRISUdX2UKGgGaAloD0MImboru2CqQkCUhpRSlGgVS+ZoFkdAmiQLHuJDV3V9lChoBmgJaA9DCP4nf/eOnXBAlIaUUpRoFU08AWgWR0CaJF0+kgwHdX2UKGgGaAloD0MIs0EmGflPckCUhpRSlGgVTXABaBZHQJokmhUR3/x1ZS4="
74
+ },
75
+ "ep_success_buffer": {
76
+ ":type:": "<class 'collections.deque'>",
77
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
78
+ },
79
+ "_n_updates": 248,
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
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e70aeba9698b7c08fecb7699b51dc48d0763e4627655dbbc94eadb96fea8804b
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:82d64f2335607b3fc3d96b34d29b9c989e7f01f3bd76da1714d3983095fdf036
3
+ size 43393
ppo-LunarLander-v2/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/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (195 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 259.6131443069445, "std_reward": 17.907591243381813, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-15T01:09:46.739127"}