NikitaBaramiia commited on
Commit
370d8e5
1 Parent(s): 456d6f9

upload first agent

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
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: 290.89 +/- 14.45
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:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7fe814ef1560>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe814ef15f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe814ef1680>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe814ef1710>", "_build": "<function ActorCriticPolicy._build at 0x7fe814ef17a0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe814ef1830>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe814ef18c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe814ef1950>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe814ef19e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe814ef1a70>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe814ef1b00>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe814f3f7e0>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1654272585.4103775, "learning_rate": 0.0001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVjQIAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxBLCIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUIAAgAAGhOzvTt9Rj8FoIW95KwHv68GCL5LUEM8AAAAAAAAAAAgIAg+v6K/P55vDD8/4gC+Y58qPrszbT4AAAAAAAAAADMSEb2pWk68soz8POl6nr2DV9k71sIkPQAAgD8AAIA/5sB0vcOVJLwG2Xq7G6KLO/ZanD2+uoO8AACAPwAAgD+awIC9riWvugjm9bScyIWw4tlyOhAfXzQAAIA/AACAP428hz4tbS8/FhYGvlMgB7/+RJI+8mfnvQAAAAAAAAAAmgXju1uFmLx9kte7IId3PZd3o7sOZNi6AACAPwAAgD/aM429cQ0SuxpvnTzI5YM8gBMxPPZCZL0AAIA/AACAP5rHwrw2sHy8DkuvPZZiJj3AzeK9WEQCPgAAgD8AAIA/wLE8vvEC6D0xcMA+QwanvqIpUrtalck9AAAAAAAAAAAzdMa8h2yfPtOX/rxycLS+bBF5vCD2zzwAAAAAAAAAAE0nXT0piVw9md+IvlX1jL5iUFK9P38hvQAAAAAAAAAAZklAPRSghboGHx46x3zStUnEPbqYlTe5AACAPwAAAADNLK26PesIu9m2PbxPqIo8GmpPPB4pcL0AAIA/AACAP5qW6bwUPaa8LXlJPLG0dT3z4c+7sOFTOwAAgD8AAIA/us4CPpHAIj4zANW++mSXvqUBk73+LPW9AAAAAAAAAACUdJRiLg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 620, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
model_1.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:112b80f1cd15ffc7161e460aa8f1163a3b540fa5276c9cd38626b501868dcae7
3
+ size 144102
model_1/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
model_1/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
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 0x7fe814ef1560>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe814ef15f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe814ef1680>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe814ef1710>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fe814ef17a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fe814ef1830>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe814ef18c0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fe814ef1950>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe814ef19e0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe814ef1a70>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe814ef1b00>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fe814f3f7e0>"
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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 2031616,
46
+ "_total_timesteps": 2000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1654272585.4103775,
51
+ "learning_rate": 0.0001,
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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 620,
79
+ "n_steps": 2048,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.95,
82
+ "ent_coef": 0.0,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 10,
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
+ }
model_1/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5941106d140225acec7eaabf045792fbd5555faa16807592cfb23b090a45cac6
3
+ size 84893
model_1/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ad5bd8cb723f8c7ec613cf4f6cc262836b518f164b86fb28cf0ea43675563b3c
3
+ size 43201
model_1/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
model_1/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: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8f93abc9d9f0cf17fece14febc6d4b9d9843836cff53cca48b00dbb71782ad17
3
+ size 219617
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 290.8878965926726, "std_reward": 14.45190979549144, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-03T16:51:50.460519"}