zxcvasd commited on
Commit
b7d6b68
1 Parent(s): 577545d

Upload PPO LunarLander-v2 trained 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: 278.40 +/- 16.59
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 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 0x7f54bc3eb160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f54bc3eb1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f54bc3eb280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f54bc3eb310>", "_build": "<function ActorCriticPolicy._build at 0x7f54bc3eb3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f54bc3eb430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f54bc3eb4c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f54bc3eb550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f54bc3eb5e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f54bc3eb670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f54bc3eb700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f54bc3e8270>"}, "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": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670343768587870346, "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": -0.007616000000000067, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 492, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "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:fa77b51f319fb29ab83836a77dd1a1189399915a83a4f38a4c09e72cdefdd4da
3
+ size 147058
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 0x7f54bc3eb160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f54bc3eb1f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f54bc3eb280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f54bc3eb310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f54bc3eb3a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f54bc3eb430>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f54bc3eb4c0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f54bc3eb550>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f54bc3eb5e0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f54bc3eb670>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f54bc3eb700>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f54bc3e8270>"
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": 2015232,
46
+ "_total_timesteps": 2000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670343768587870346,
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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADP4rDyf/Qk+aDdgvvZ+0r4UVAC+IDLhvAAAAAAAAAAAJqnIvYKzpz/+3ni+lJcRvzY0qL1i7F29AAAAAAAAAAAzrWS8wx8VPQoJjLxSBYe+yQiwvVRyEj0AAAAAAAAAACA4S74krwI+w7zfPtbdcL7fmYG96u0hPgAAAAAAAAAAGi1tvVJQ0ruC77k+oDpVvmlRxDvYjoe+AACAPwAAgD+Axdg9vaIePxGbnr0Wwrm+pHmKPUJPYL0AAAAAAAAAAADkp70nD7g/SqgPv/KSs73Brpm8GuDzvQAAAAAAAAAAZhjUPLAMtT81Hc09MAmuvgJE4z2CjkA9AAAAAAAAAACzdgK+z3d+Pc3+nj6kU2++m3wfvOWf4DsAAAAAAAAAAM3sCbsswqo/AhxGvcQvA7+Bfpo8tjnbPQAAAAAAAAAAACY4vCGakrxrLOY9vAsdvDmk/r3Alvq8AACAPwAAgD9aUio+LBddP0SzS7z5t9e+vhz0Pf+rEr4AAAAAAAAAAJo/+TycmiQ/xVP8vXrN577H9+k8Bf1vvQAAAAAAAAAAABYXPIXb6rkazCa06SCMrzeZIzs5zZUzAACAPwAAgD9a7S0+6JmfP/Jo2T5n2OS+TcasPuWVHT4AAAAAAAAAAM1aNLzOdrE/lkYZviLocL7A0fm7trRDvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
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": -0.007616000000000067,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 492,
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:": "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"
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 sha256:235c612e8b5d5bcfb16e79201b2bc5e047353592383e4aa9531c10b261631122
3
+ size 87865
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ea68de64c76bb21e06a0d65c1119e4dfb428ca9b04a968a0c1feee068612f2e
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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.8.15
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.12.1+cu113
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": 278.3998827848185, "std_reward": 16.585760676855234, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-06T16:59:23.708229"}