shoop commited on
Commit
c14ec6c
·
1 Parent(s): cfd87fd

Colab default training for unit 1

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: 216.31 +/- 79.92
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 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 0x7f6a8b7178c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6a8b717950>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6a8b7179e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6a8b717a70>", "_build": "<function ActorCriticPolicy._build at 0x7f6a8b717b00>", "forward": "<function ActorCriticPolicy.forward at 0x7f6a8b717b90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6a8b717c20>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6a8b717cb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6a8b717d40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6a8b717dd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6a8b717e60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6a8b757e70>"}, "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": 1662053428.759755, "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": 124, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.6.0", "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:c02f80764f464f2b3cafb2858c05cfeaef90888b83e2f9da5b5e7224267a8683
3
+ size 147139
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.0
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 0x7f6a8b7178c0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6a8b717950>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6a8b7179e0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6a8b717a70>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f6a8b717b00>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f6a8b717b90>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6a8b717c20>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f6a8b717cb0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6a8b717d40>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6a8b717dd0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6a8b717e60>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f6a8b757e70>"
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": 1662053428.759755,
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": 124,
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:aaaf2b96da4d142a400351b17bcfea8a21178f2d60dcc26c91acd468706d961a
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:ba6cbd1db55e467002e313fd14ab1c6d022639937a1ce5d4297762a2b50f75cf
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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.6.0
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 (190 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 216.31290121256242, "std_reward": 79.92378320324181, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-09-01T18:01:22.832339"}