vk21 commited on
Commit
48f80a1
1 Parent(s): fee4064

Initial Commit

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: 225.89 +/- 47.17
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 0x7f44feebadc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f44feebae50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f44feebaee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f44feebaf70>", "_build": "<function ActorCriticPolicy._build at 0x7f44fee3e040>", "forward": "<function ActorCriticPolicy.forward at 0x7f44fee3e0d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f44fee3e160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f44fee3e1f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f44fee3e280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f44fee3e310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f44fee3e3a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f44fee3e430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f44feeb94e0>"}, "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": 1676484775822722234, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJMqfD5yaxc/ILT7vY4FhL42GKU9nYP9vAAAAAAAAAAAM8vGu48WdbpiUNW6OoADtl2neDqSuPk5AACAPwAAgD+axk+9j45Lui6+tbpzQ7K1q/baulKR1jkAAIA/AACAP4AeWb32GGy66k6kOxLPXDiIOQe7wvgVuAAAgD8AAIA/M1D7vK51gLoh+w07PESatOh/mrq3YiK6AACAPwAAgD+AtLi9uCakuXhlgbqRrc213rzMO4NImDkAAIA/AAAAADP48jwUDuS4AniGu7zvMDZo1v84B2ifOgAAgD8AAIA/O3rIvqvfDz8AwFQ9rOWJvqhXmL1KXow9AAAAAAAAAAANZbO9XO9VumxRirse4US2Kec2OwziojoAAAAAAAAAAGb/97x7yJi6sGXqOtHU17V85uc6Ix0GugAAgD8AAIA/s4FnPhjNWj96Pvo72rqjvnilHz6BsIS7AAAAAAAAAAAA5xy+2tw1PrAPaT5HAgm+Lf2nPNnrE70AAAAAAAAAAAuL6b5AFiM/GfyEu0D/fL4D37u9nQAFPgAAAAAAAAAAM7gGva4PjLpQsnE53t3rr/Mm/roKJ4q4AACAPwAAgD/mfWO9jzo2ugBeQjkVfOw0jdB6O6aGYLgAAIA/AACAP2b6HrwydYA+mlO4PEDTL76KJbq8Yhd7vQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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-5.10.147+-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 sha256:903d1013ac7c85100fa3f1744eaf7dbd7ea243d0c77b0020d3dead9cc070156c
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 0x7f44feebadc0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f44feebae50>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f44feebaee0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f44feebaf70>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f44fee3e040>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f44fee3e0d0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f44fee3e160>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f44fee3e1f0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f44fee3e280>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f44fee3e310>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f44fee3e3a0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f44fee3e430>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f44feeb94e0>"
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": 1676484775822722234,
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:": "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"
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:cb8430ff1b51d8009321c92021395123229f5d0ff8dade52e42e6b455e17fe37
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:b9480d1ccc61d794d5e63a454008265bcbf2b9fb31bcb7591a785fee2ade5730
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 (237 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 225.88699531661018, "std_reward": 47.169898591041374, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-15T18:44:38.686228"}