alexdavey commited on
Commit
a1dd9df
1 Parent(s): b38c89c

Upload PPO LunarLander-v2 trained agent

Browse files
README.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - metrics:
12
+ - type: mean_reward
13
+ value: 245.24 +/- 18.40
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **PPO** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
26
+
27
+ ## Usage (with Stable-baselines3)
28
+ TODO: Add your code
29
+
30
+
31
+ ```python
32
+ from stable_baselines3 import ...
33
+ from huggingface_sb3 import load_from_hub
34
+
35
+ ...
36
+ ```
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 0x7f1490832040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f14908320d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1490832160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f14908321f0>", "_build": "<function ActorCriticPolicy._build at 0x7f1490832280>", "forward": "<function ActorCriticPolicy.forward at 0x7f1490832310>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f14908323a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1490832430>", "_predict": "<function ActorCriticPolicy._predict at 0x7f14908324c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1490832550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f14908325e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1490832670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f14908334c0>"}, "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": 1674591479854614447, "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-5.4.0-122-generic-x86_64-with-glibc2.31 # 138~18.04.1-Ubuntu SMP Fri Jun 24 14:14:03 UTC 2022", "Python": "3.9.13", "Stable-Baselines3": "1.7.0", "PyTorch": "1.12.0+cu116", "GPU Enabled": "True", "Numpy": "1.23.1", "Gym": "0.21.0"}}
replay.mp4 ADDED
Binary file (201 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 245.24130079911947, "std_reward": 18.398838758706294, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-24T20:56:41.217908"}
unit1_ppo-LunarLander-v2_AD.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a9cebd2896cdf49414baf473107add247da7ba34441d0f102286eeb2b12213e9
3
+ size 147378
unit1_ppo-LunarLander-v2_AD/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
unit1_ppo-LunarLander-v2_AD/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 0x7f1490832040>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f14908320d0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1490832160>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f14908321f0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f1490832280>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f1490832310>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f14908323a0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1490832430>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f14908324c0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1490832550>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f14908325e0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1490832670>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f14908334c0>"
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": 1674591479854614447,
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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAIB/AD3sscu7QikSPiNZZrsmu0i92g+bvgAAgD8AAIA/c+FxPtHWFj+wd36+pA9yvg7wz71FU3G9AAAAAAAAAADNFGI7yPjGPRWL0D2XhnC+rAU/PaZdWb0AAAAAAAAAADodH77Nh4c/2JR0viLWjb4EiIu+6vzTvAAAAAAAAAAA2m6jPaCEcj+zgPk84b+lvmgMkDyuxOm9AAAAAAAAAAC4SYC+OnkRP7Wfaj7CzLO+6iZSPKuY2T0AAAAAAAAAADOj5jzzjEg/vjUovdD9ub5xaK67C/tGuwAAAAAAAAAAjQTLPdfybbs4fNo7FL8oPUF0sTwqqty9AAAAAAAAgD99S3W+PIF8P25Z3L23Q6S+7JuZvlJ3zD0AAAAAAAAAAHBNYL7Yq2E/o0TRvZdso76yc12+xw63PQAAAAAAAAAAjZ7sPbqmZz+FDay8XR2ivr3lFT5ZfiW+AAAAAAAAAADmlCI97U74Pr3Zm71DRWu+Uvu9vX3ycL0AAAAAAAAAAJoVDj1IY8O6UfGeOy+jszw25Ry69VyaPQAAgD8AAIA/LZMNP+yG273izyU9MsyFuT7Tj7xJjMM6AAAAAAAAAABNmlk9xii3P3VHXj4BLYm+IFIPPopm3D0AAAAAAAAAAJp8OT5DUHG8T3ouPV8egLvrZs29GGlPvAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
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
+ }
unit1_ppo-LunarLander-v2_AD/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e8f0499888508d3d0303012823fba088697a8b2c7b39dd76b5a0423e278b9192
3
+ size 87865
unit1_ppo-LunarLander-v2_AD/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:86b7790f5afc3049c18d89bbb48430a7d414ab157ad9645216c9e8e2da8f2644
3
+ size 43393
unit1_ppo-LunarLander-v2_AD/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
unit1_ppo-LunarLander-v2_AD/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.4.0-122-generic-x86_64-with-glibc2.31 # 138~18.04.1-Ubuntu SMP Fri Jun 24 14:14:03 UTC 2022
2
+ - Python: 3.9.13
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.12.0+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.23.1
7
+ - Gym: 0.21.0