lotek93 commited on
Commit
85c631c
1 Parent(s): 0f411f6
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: MLP
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: 261.16 +/- 23.30
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **MLP** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **MLP** 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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f2d18e433a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d18e43430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d18e434c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d18e43550>", "_build": "<function ActorCriticPolicy._build at 0x7f2d18e435e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f2d18e43670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d18e43700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2d18e43790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d18e43820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d18e438b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d18e43940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2d18e3e4e0>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671398014668196183, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAABr8lL0GQ9U+2KyIO1dUn770kNW8IjCXuwAAAAAAAAAAmnTIvWfnAT+Ly7o9miiHvl6cY7yYixE+AAAAAAAAAADN3B69rLODPtviJD3OPzy+YeXPPX/MPjwAAAAAAAAAAOa3Pr4/DmI/1n7yvcQQ5L6Nvp++CCcMPgAAAAAAAAAAMzN9uSrnOD7krMa8QO2KvqoBdjwb3NK9AAAAAAAAAACm/sK9jxZ7uuWlXrmLtzC0iIzSOdxDgjgAAIA/AACAP800Kjtwiq0+YyFmvMRzlr5PU2w9IOacvQAAAAAAAAAAVnWLPhN2lj9miW0+/ZHTvotRyj7/tRS9AAAAAAAAAABmJmO6HAVVPepWLT1kgDm+riwYPYWZNz0AAAAAAAAAALO5Nz2PvTG8YfKkvfSjN72RqYI9uKt5PgAAgD8AAIA/A4RYvnNmij8rYwC/hLgMv1yd0L4ji0y+AAAAAAAAAAAzMQ+8d1UBPtPKG730j4G+o5tQO5nnrL0AAAAAAAAAAHqYF75RQRs+o2HRPo2bg77rjlk+e3pPvAAAAAAAAAAAGhsHvSM5XT/raia8+RW3vl/nWL2wKZq8AAAAAAAAAABNDgk9j7YUuvpdTDsCCY43ho9OOnbZILoAAIA/AACAP1NhDr7p0mK8SoJfvT6OPjy4SMI9YgsbvQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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-5.15.0-56-generic-x86_64-with-glibc2.29 #62~20.04.1-Ubuntu SMP Tue Nov 22 21:24:20 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu116", "GPU Enabled": "True", "Numpy": "1.23.2", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:946ff744d2721c40130466d56c93aa48ce9459edb07083f07bcdefea40a98b0f
3
+ size 147184
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f2d18e433a0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d18e43430>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d18e434c0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d18e43550>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f2d18e435e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f2d18e43670>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d18e43700>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f2d18e43790>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d18e43820>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d18e438b0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d18e43940>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f2d18e3e4e0>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 507904,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1671398014668196183,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.015808000000000044,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "gAWVbRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIg6W6gJfXcUCUhpRSlIwBbJRL64wBdJRHQJHBtQ9A5aN1fZQoaAZoCWgPQwgyyF2EqStyQJSGlFKUaBVNBAFoFkdAkcHuhbnoxHV9lChoBmgJaA9DCHNIaqHkOm5AlIaUUpRoFUv/aBZHQJHCt6u4gA91fZQoaAZoCWgPQwhvDtdqjzVyQJSGlFKUaBVNmgFoFkdAkcMHAqNIb3V9lChoBmgJaA9DCCh+jLlrZnJAlIaUUpRoFU1bAWgWR0CRwxiqQzUJdX2UKGgGaAloD0MIfsaFA6Efb0CUhpRSlGgVTVEBaBZHQJHDmtq59Vp1fZQoaAZoCWgPQwg97lutk9RvQJSGlFKUaBVNOwFoFkdAkcP7lJYkmnV9lChoBmgJaA9DCLDjv0AQ9W5AlIaUUpRoFU0pAWgWR0CRxHmm+CbudX2UKGgGaAloD0MIycuaWGDmbUCUhpRSlGgVTSQBaBZHQJHEvjaPCEZ1fZQoaAZoCWgPQwgDYDyDBslsQJSGlFKUaBVNJQFoFkdAkcTVFx4pt3V9lChoBmgJaA9DCNY73A6NDm9AlIaUUpRoFU0wAWgWR0CRxPpR4yGjdX2UKGgGaAloD0MIh2wgXewkbUCUhpRSlGgVTRcBaBZHQJHFLxLCemN1fZQoaAZoCWgPQwigbwuWqtBwQJSGlFKUaBVNAQFoFkdAkcX3Y+Sr53V9lChoBmgJaA9DCCXP9X34wHBAlIaUUpRoFU0FAWgWR0CRxj5IYm9hdX2UKGgGaAloD0MIBRiWP18lb0CUhpRSlGgVTQwBaBZHQJHGn8k2P1d1fZQoaAZoCWgPQwjBrbt5apJxQJSGlFKUaBVNOwFoFkdAkcbfDHfdh3V9lChoBmgJaA9DCMEAwoeSzHJAlIaUUpRoFU1gAWgWR0CRxweKKpDNdX2UKGgGaAloD0MIsW1RZkM7cECUhpRSlGgVTTcBaBZHQJHHIhY/3WZ1fZQoaAZoCWgPQwgGoFG6tJFzQJSGlFKUaBVNIQFoFkdAkcfKt1ZDA3V9lChoBmgJaA9DCINpGD6iOG5AlIaUUpRoFU0PAWgWR0CRx9R8MNMHdX2UKGgGaAloD0MIDCB8KNEqcUCUhpRSlGgVS/FoFkdAkcfaiO/+KnV9lChoBmgJaA9DCCo7/aCuw25AlIaUUpRoFU1CAWgWR0CRyJjCHh0hdX2UKGgGaAloD0MIoyB4fHuHcUCUhpRSlGgVTQYBaBZHQJHJnVJ+UhV1fZQoaAZoCWgPQwgtQUZABYBsQJSGlFKUaBVNGgFoFkdAkcm9a+vhZXV9lChoBmgJaA9DCOuOxTYp3HFAlIaUUpRoFU1UAWgWR0CRygumJm/WdX2UKGgGaAloD0MIYoVbPpIqckCUhpRSlGgVTT8BaBZHQJHKKh4+r2h1fZQoaAZoCWgPQwh80R4v5EpyQJSGlFKUaBVNLwFoFkdAkco37Hhjv3V9lChoBmgJaA9DCGWNeohGTG5AlIaUUpRoFU0yAWgWR0CRyqNHpbD/dX2UKGgGaAloD0MILEfIQB6ibECUhpRSlGgVS/hoFkdAkcq2uHN5dHV9lChoBmgJaA9DCI85z9gX9XFAlIaUUpRoFUv9aBZHQJHLGW5Yoy91fZQoaAZoCWgPQwgK8rORa5NvQJSGlFKUaBVL+mgWR0CRy2R8twrEdX2UKGgGaAloD0MImN7+XHRcckCUhpRSlGgVTTgBaBZHQJHLeFtbcGl1fZQoaAZoCWgPQwg75Ga4wfVwQJSGlFKUaBVNGQFoFkdAkcu8rmQr+nV9lChoBmgJaA9DCGwGuCBb625AlIaUUpRoFU0IAWgWR0CRzEyckMTfdX2UKGgGaAloD0MINez3xDq7cECUhpRSlGgVTREBaBZHQJHMbrAxi5N1fZQoaAZoCWgPQwguy9dl+NFTQJSGlFKUaBVLoWgWR0CRzUVNYbKidX2UKGgGaAloD0MIMA+Z8qFIcUCUhpRSlGgVTXwBaBZHQJHNqR3eN1h1fZQoaAZoCWgPQwg/yLJg4utwQJSGlFKUaBVNSwFoFkdAkc5mdmQKbHV9lChoBmgJaA9DCKwA323em29AlIaUUpRoFU1/AWgWR0CRznYfnwG4dX2UKGgGaAloD0MIlG3gDhQ2cECUhpRSlGgVTRUBaBZHQJHOf5k9U0h1fZQoaAZoCWgPQwgqVaLsrXRyQJSGlFKUaBVNBwFoFkdAkdn8Aiml7HV9lChoBmgJaA9DCEKUL2jhinNAlIaUUpRoFU0TAWgWR0CR2hDn/1g6dX2UKGgGaAloD0MI7swEw7k3bkCUhpRSlGgVTTcBaBZHQJHaSW4Vh1F1fZQoaAZoCWgPQwhqFf2hWfNxQJSGlFKUaBVNMAFoFkdAkdqryhBZ6nV9lChoBmgJaA9DCMhFtYioMXBAlIaUUpRoFU0rAWgWR0CR2wFN+LFXdX2UKGgGaAloD0MIh/4JLlYvcECUhpRSlGgVS/xoFkdAkdsIl6Z6U3V9lChoBmgJaA9DCN+KxAR1tXBAlIaUUpRoFUvtaBZHQJHbJBZ6lch1fZQoaAZoCWgPQwgN/RNcrGJxQJSGlFKUaBVNIwFoFkdAkdtSvLX+VHV9lChoBmgJaA9DCBEebRxxknNAlIaUUpRoFU0QAWgWR0CR22KBd2PldX2UKGgGaAloD0MIcy8wK1QOckCUhpRSlGgVS/VoFkdAkdu1hoduHnV9lChoBmgJaA9DCAOTG0WWpnBAlIaUUpRoFU0vAWgWR0CR3LnTiKixdX2UKGgGaAloD0MI7ZqQ1phkcECUhpRSlGgVTQYBaBZHQJHc4Ouq3mV1fZQoaAZoCWgPQwjudr00RdtvQJSGlFKUaBVNGQFoFkdAkd2OfNA1N3V9lChoBmgJaA9DCJmEC3mEInFAlIaUUpRoFUvyaBZHQJHdwbHZK4B1fZQoaAZoCWgPQwiGHjF6rgByQJSGlFKUaBVNDQFoFkdAkd4I4ACGOHV9lChoBmgJaA9DCKMFaFsNg3BAlIaUUpRoFU0MAWgWR0CR3k2Zy+6AdX2UKGgGaAloD0MI1v7O9uhHcUCUhpRSlGgVTSABaBZHQJHeaBczImx1fZQoaAZoCWgPQwhiZTTyuZxwQJSGlFKUaBVNFgFoFkdAkd6xkd3jdnV9lChoBmgJaA9DCAHBHD2+qHNAlIaUUpRoFU1eAWgWR0CR31k3S8aodX2UKGgGaAloD0MIUMO3sO4Bc0CUhpRSlGgVTSUBaBZHQJHfXf+CK791fZQoaAZoCWgPQwgJUb6gRX1yQJSGlFKUaBVNDwFoFkdAkd9eQ+2VmnV9lChoBmgJaA9DCJG5Mqg2cG5AlIaUUpRoFU0WAWgWR0CR33Grjo6kdX2UKGgGaAloD0MIprVpbC+wckCUhpRSlGgVTQMBaBZHQJHfe5RTCLx1fZQoaAZoCWgPQwgY0uEhzDhyQJSGlFKUaBVNHwFoFkdAkd+sIqsls3V9lChoBmgJaA9DCNSdJ56zBXFAlIaUUpRoFU0uAWgWR0CR4BdBBzFNdX2UKGgGaAloD0MInNuEe+V8cUCUhpRSlGgVTTkBaBZHQJHgnK1XvH91fZQoaAZoCWgPQwg0ngjiPKdxQJSGlFKUaBVL8mgWR0CR4Kq9XcQAdX2UKGgGaAloD0MIF2L1R1jscECUhpRSlGgVTS0BaBZHQJHhdt4zJp51fZQoaAZoCWgPQwig/x68dhtxQJSGlFKUaBVNEAFoFkdAkeH85bQkX3V9lChoBmgJaA9DCC6PNSPDDnFAlIaUUpRoFU0GAWgWR0CR4oWOZLIxdX2UKGgGaAloD0MI4xdeSTJVckCUhpRSlGgVTRoBaBZHQJHizutwJgN1fZQoaAZoCWgPQwir6Xqi63ZvQJSGlFKUaBVNOQFoFkdAkeMfY4ACGXV9lChoBmgJaA9DCEsfuqC+AG1AlIaUUpRoFU1hAWgWR0CR42Adn004dX2UKGgGaAloD0MI9kNssLDwcECUhpRSlGgVS/loFkdAkeNpyU9py3V9lChoBmgJaA9DCCjwTj69+nBAlIaUUpRoFUv9aBZHQJHjfMKTjed1fZQoaAZoCWgPQwj0qWOVUnBvQJSGlFKUaBVNKwFoFkdAkeOXMEA5rHV9lChoBmgJaA9DCHdqLjcYjG9AlIaUUpRoFU0QAWgWR0CR48WJJoTPdX2UKGgGaAloD0MIsHCS5s+XcECUhpRSlGgVS/5oFkdAkePba/RE4XV9lChoBmgJaA9DCOdxGMxfuXJAlIaUUpRoFU0UAWgWR0CR4+lr/KhddX2UKGgGaAloD0MI2ozTEJUWckCUhpRSlGgVTSIBaBZHQJHkHtTkyUN1fZQoaAZoCWgPQwgWwmosYVttQJSGlFKUaBVNJgFoFkdAkeTcCYCyQnV9lChoBmgJaA9DCOlfksqU6G5AlIaUUpRoFU0FAWgWR0CR5P17IDHPdX2UKGgGaAloD0MIQfM5d7uuUECUhpRSlGgVS9xoFkdAkeUdJWeYlnV9lChoBmgJaA9DCDbknxnEaG5AlIaUUpRoFU0rAWgWR0CR5XlaKUFCdX2UKGgGaAloD0MIn1bRH5ohMUCUhpRSlGgVS8toFkdAkeWqHTI/7nV9lChoBmgJaA9DCMYVF0flT3JAlIaUUpRoFU0KAWgWR0CR5jNNJvpAdX2UKGgGaAloD0MIZ0gVxasmc0CUhpRSlGgVS+hoFkdAkebN8VpKz3V9lChoBmgJaA9DCPEpAMYzW25AlIaUUpRoFU0GAWgWR0CR5x+IMz/IdX2UKGgGaAloD0MIXTKOkSx+cECUhpRSlGgVTRkBaBZHQJHnLjm0VrR1fZQoaAZoCWgPQwgZxXJLK8pvQJSGlFKUaBVNDAFoFkdAked+nhsImnV9lChoBmgJaA9DCFsjgnFwTnFAlIaUUpRoFU0MAWgWR0CR55C66J66dX2UKGgGaAloD0MIEOZ2LzdkcUCUhpRSlGgVTREBaBZHQJHnvXBguyx1fZQoaAZoCWgPQwimCdtPxiFuQJSGlFKUaBVL/2gWR0CR586uGKyfdX2UKGgGaAloD0MIZmZmZqbYcUCUhpRSlGgVTQ4BaBZHQJHn9fJFLFp1fZQoaAZoCWgPQwimZDkJJZltQJSGlFKUaBVNJAFoFkdAkegu8PFvRHV9lChoBmgJaA9DCADl797RHHJAlIaUUpRoFU0LAWgWR0CR6Ddv863idX2UKGgGaAloD0MIOwFNhM1ZckCUhpRSlGgVTRYBaBZHQJHpIvL5h0B1fZQoaAZoCWgPQwhHVKhu7vBwQJSGlFKUaBVNEQFoFkdAkek0r08NhHV9lChoBmgJaA9DCHiAJy2cT3FAlIaUUpRoFUv0aBZHQJHpSbQTmGN1fZQoaAZoCWgPQwhRTN4Ac31yQJSGlFKUaBVNGwFoFkdAkemC5NGmUHVlLg=="
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 248,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 4,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "gAWVzwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjE8vaG9tZS9tYWRkLy5sb2NhbC9saWIvcHl0aG9uMy44L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxPL2hvbWUvbWFkZC8ubG9jYWwvbGliL3B5dGhvbjMuOC9zaXRlLXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGggfZR9lChoF2gOjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoGIwHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b25f950c5e4a6aacd00395b2e2653df56e02f7323ece6fc4ca48daba2da3df76
3
+ size 87865
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ecd7de45f3b2710aa596ebe2fac15b9a9eeb93cd66db65d65c5bd9e4a5a0e3b4
3
+ size 43201
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-5.15.0-56-generic-x86_64-with-glibc2.29 #62~20.04.1-Ubuntu SMP Tue Nov 22 21:24:20 UTC 2022
2
+ Python: 3.8.10
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.12.1+cu116
5
+ GPU Enabled: True
6
+ Numpy: 1.23.2
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (240 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 261.1551259650475, "std_reward": 23.30202885548722, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-19T01:30:49.957503"}