katta commited on
Commit
d9f1d6e
1 Parent(s): 8af64c3

Add Unit 1 trained model to hub

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
PPO-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d3c2dbe2302a8366c75013154c1de09dc614cd51368c180222b3d9ac2174a245
3
+ size 144102
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 0x7f1628e525f0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1628e52680>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1628e52710>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1628e527a0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f1628e52830>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f1628e528c0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1628e52950>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f1628e529e0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1628e52a70>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1628e52b00>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1628e52b90>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f1628e17a20>"
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": 212992,
46
+ "_total_timesteps": 200000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1651750032.2338035,
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": -0.0649599999999999,
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": 332,
79
+ "n_steps": 1024,
80
+ "gamma": 0.995,
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 sha256:1d43e1ac94bb3c26c6b06513c7d154fef28543d05e48d743381e0d19e42c626e
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:f55fb41b98561487b9ac10f66a75ebd9aeab9e645e82cafb994c3ecd7736bce1
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
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-mlp
10
+ results:
11
+ - metrics:
12
+ - type: mean_reward
13
+ value: 272.32 +/- 16.75
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-mlp** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO-mlp** 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 0x7f1628e525f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1628e52680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1628e52710>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1628e527a0>", "_build": "<function ActorCriticPolicy._build at 0x7f1628e52830>", "forward": "<function ActorCriticPolicy.forward at 0x7f1628e528c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1628e52950>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1628e529e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1628e52a70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1628e52b00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1628e52b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f1628e17a20>"}, "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": 212992, "_total_timesteps": 200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651750032.2338035, "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": -0.0649599999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 332, "n_steps": 1024, "gamma": 0.995, "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"}}
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f4a535d41d52dfd66b83caffdc9e313209597d94de5e38f99a1c2b3d45245644
3
+ size 204673
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 272.3175568365841, "std_reward": 16.745716085886404, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T11:33:13.062724"}