ironbar commited on
Commit
5dc351f
1 Parent(s): 0aca5ef

trying to upload my first model

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 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: 281.55 +/- 12.93
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** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
25
+
26
+ ## Usage (with Stable-baselines3)
27
+ TODO: Add your code
28
+
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 0x7f3fa9d2fd40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3fa9d2fdd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3fa9d2fe60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3fa9d2fef0>", "_build": "<function ActorCriticPolicy._build at 0x7f3fa9d2ff80>", "forward": "<function ActorCriticPolicy.forward at 0x7f3fa9d38050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3fa9d380e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3fa9d38170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3fa9d38200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3fa9d38290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3fa9d38320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f3fa9d8c180>"}, "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": 4014080, "_total_timesteps": 4000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651907918.357424, "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": -0.0035199999999999676, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1968, "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": "1.5.0", "PyTorch": "1.11.0+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 sha256:327c04299c03cfba26b7cd58b70a5d2b46c1de87d50ccc988571d9f1682e811b
3
+ size 143983
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
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 0x7f3fa9d2fd40>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3fa9d2fdd0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3fa9d2fe60>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3fa9d2fef0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f3fa9d2ff80>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f3fa9d38050>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3fa9d380e0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f3fa9d38170>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3fa9d38200>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3fa9d38290>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3fa9d38320>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f3fa9d8c180>"
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": 4014080,
46
+ "_total_timesteps": 4000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1651907918.357424,
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": -0.0035199999999999676,
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": 1968,
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 sha256:3315565174c4fe24f13a5e7c91facc83cc614641a26acb6544520836bbb59e0f
3
+ size 84893
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e7920550cd37af99682ec73a2d9d5019fd1ca344963886fe974f24fa4c67b1a6
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: 1.5.0
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 sha256:1b624f70480a3810a37ae4bcbd387039bf877bb7f23753962cf66963e4bb6a0c
3
+ size 199687
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 281.55323083734095, "std_reward": 12.92734753799479, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-07T07:59:11.727887"}