sujit27 commited on
Commit
0b0a25a
1 Parent(s): 86e9f69

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: 246.07 +/- 25.56
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 0x7f09216a0200>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f09216a0290>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f09216a0320>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f09216a03b0>", "_build": "<function ActorCriticPolicy._build at 0x7f09216a0440>", "forward": "<function ActorCriticPolicy.forward at 0x7f09216a04d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f09216a0560>", "_predict": "<function ActorCriticPolicy._predict at 0x7f09216a05f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f09216a0680>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f09216a0710>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f09216a07a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f09216f9570>"}, "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": 1666083160600723261, "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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v1.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a16950ee0cccadf716072cfe6db9ae78b4f310211ad78a3bbe9f723ea322c2a
3
+ size 147156
ppo-LunarLander-v1/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v1/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 0x7f09216a0200>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f09216a0290>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f09216a0320>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f09216a03b0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f09216a0440>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f09216a04d0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f09216a0560>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f09216a05f0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f09216a0680>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f09216a0710>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f09216a07a0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f09216f9570>"
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": 1015808,
46
+ "_total_timesteps": 1000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1666083160600723261,
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:": "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"
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:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v1/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:23cbe10b9ae78faa77757a1b923d3910d558896b21251a46f831c120a34fd525
3
+ size 87865
ppo-LunarLander-v1/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c48b1a4d35f3b116f351dbcee659e5c420cd741bd2a28272c4b762ae50efd8be
3
+ size 43201
ppo-LunarLander-v1/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-v1/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.7.15
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 (260 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 246.0654633373809, "std_reward": 25.56439204138466, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-18T09:16:51.925245"}