yweslakarep commited on
Commit
41acb83
1 Parent(s): 45094cf

Upload PPO LunarLander-v2 trained agent

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: -46.68 +/- 49.68
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}", "__doc__": "\n Policy class with Q-Value Net and target net for DQN\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 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 DQNPolicy.__init__ at 0x7cd03b7d75b0>", "_build": "<function DQNPolicy._build at 0x7cd03b7d7640>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7cd03b7d76d0>", "forward": "<function DQNPolicy.forward at 0x7cd03b7d7760>", "_predict": "<function DQNPolicy._predict at 0x7cd03b7d77f0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7cd03b7d7880>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7cd03b7d7910>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cd03b7e1580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712571112908282087, "learning_rate": 0.0005, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 4064, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 15610, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "buffer_size": 10000, "batch_size": 64, "learning_starts": 1000, "tau": 1.0, "gamma": 0.999, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ", "__init__": "<function ReplayBuffer.__init__ at 0x7cd03b9b3a30>", "add": "<function ReplayBuffer.add at 0x7cd03b9b3ac0>", "sample": "<function ReplayBuffer.sample at 0x7cd03b9b3b50>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7cd03b9b3be0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cd03b7d0640>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 625, "_n_calls": 62500, "max_grad_norm": 10, "exploration_rate": 0.05, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:85085c56a6db01641f9e4e7e108024f83ee3d3922fca76927ea48cc4af504acc
3
+ size 107894
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.dqn.policies",
6
+ "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}",
7
+ "__doc__": "\n Policy class with Q-Value Net and target net for DQN\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 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 ",
8
+ "__init__": "<function DQNPolicy.__init__ at 0x7cd03b7d75b0>",
9
+ "_build": "<function DQNPolicy._build at 0x7cd03b7d7640>",
10
+ "make_q_net": "<function DQNPolicy.make_q_net at 0x7cd03b7d76d0>",
11
+ "forward": "<function DQNPolicy.forward at 0x7cd03b7d7760>",
12
+ "_predict": "<function DQNPolicy._predict at 0x7cd03b7d77f0>",
13
+ "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7cd03b7d7880>",
14
+ "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7cd03b7d7910>",
15
+ "__abstractmethods__": "frozenset()",
16
+ "_abc_impl": "<_abc._abc_data object at 0x7cd03b7e1580>"
17
+ },
18
+ "verbose": 1,
19
+ "policy_kwargs": {},
20
+ "num_timesteps": 1000000,
21
+ "_total_timesteps": 1000000,
22
+ "_num_timesteps_at_start": 0,
23
+ "seed": null,
24
+ "action_noise": null,
25
+ "start_time": 1712571112908282087,
26
+ "learning_rate": 0.0005,
27
+ "tensorboard_log": null,
28
+ "_last_obs": {
29
+ ":type:": "<class 'numpy.ndarray'>",
30
+ ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADYR8D6Yka29mGYWv8tYM78/v8g+0F86vQAAAAAAAAAAJizWvmohQD4j5QO/leSRv/XqFz0HGg+9AAAAAAAAAABaWZw9rPSfP6bUaD72qSS/ocNFO7JUjjwAAAAAAAAAAE0Kub6Jrhg/DYb3vjDhrr+ZEJg9qPR+vQAAAAAAAAAAtiBaP4vAEj/IxRO7pTmHvTGFrj5TrwU+AAAAAAAAAAAaPZy9BCnpPV4Khb7vP1W/4fkAPu3TxLsAAAAAAAAAALbmBT9s6Bg/9eWRPiblbL2ljiU+A7dhPQAAAAAAAAAARsccvgw8Jz4eH6O+7ws9v8REoD3G12a8AAAAAAAAAADg6xw+aDXavN71pb7KIvi+W4H5utHXwr8AAAAAAACAPzpwRj8HrQk/aCd9PcxUmLzxTp4+KZEGPgAAAAAAAAAAU7pVP0nMnT6s9Jm+FsIXv8QgDD82XWM7AAAAAAAAAAAmhCQ/7FdyvhVc1j2ZMX+9qNGnPgYaqL4AAAAAAACAP+1TtD5x73A8LBvIvnTvB7/oCqo+IyJevQAAAAAAAAAAprGWvWYSUz8uv3K+SQ2Uv4gKvD1DXcU8AAAAAAAAAAAAwGC6AeW0P/1yhbyDZQG/FP2XPNMTgz0AAAAAAAAAAIaGPz+4mQw/HVjgPnvJGj2R00Q+3uupPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
31
+ },
32
+ "_last_episode_starts": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_original_obs": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "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"
39
+ },
40
+ "_episode_num": 4064,
41
+ "use_sde": false,
42
+ "sde_sample_freq": -1,
43
+ "_current_progress_remaining": 0.0,
44
+ "_stats_window_size": 100,
45
+ "ep_info_buffer": {
46
+ ":type:": "<class 'collections.deque'>",
47
+ ":serialized:": "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"
48
+ },
49
+ "ep_success_buffer": {
50
+ ":type:": "<class 'collections.deque'>",
51
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
52
+ },
53
+ "_n_updates": 15610,
54
+ "observation_space": {
55
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
56
+ ":serialized:": "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",
57
+ "dtype": "float32",
58
+ "bounded_below": "[ True True True True True True True True]",
59
+ "bounded_above": "[ True True True True True True True True]",
60
+ "_shape": [
61
+ 8
62
+ ],
63
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
64
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
65
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
66
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
67
+ "_np_random": null
68
+ },
69
+ "action_space": {
70
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
71
+ ":serialized:": "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",
72
+ "n": "4",
73
+ "start": "0",
74
+ "_shape": [],
75
+ "dtype": "int64",
76
+ "_np_random": "Generator(PCG64)"
77
+ },
78
+ "n_envs": 16,
79
+ "buffer_size": 10000,
80
+ "batch_size": 64,
81
+ "learning_starts": 1000,
82
+ "tau": 1.0,
83
+ "gamma": 0.999,
84
+ "gradient_steps": 1,
85
+ "optimize_memory_usage": false,
86
+ "replay_buffer_class": {
87
+ ":type:": "<class 'abc.ABCMeta'>",
88
+ ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
89
+ "__module__": "stable_baselines3.common.buffers",
90
+ "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ",
91
+ "__init__": "<function ReplayBuffer.__init__ at 0x7cd03b9b3a30>",
92
+ "add": "<function ReplayBuffer.add at 0x7cd03b9b3ac0>",
93
+ "sample": "<function ReplayBuffer.sample at 0x7cd03b9b3b50>",
94
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7cd03b9b3be0>",
95
+ "__abstractmethods__": "frozenset()",
96
+ "_abc_impl": "<_abc._abc_data object at 0x7cd03b7d0640>"
97
+ },
98
+ "replay_buffer_kwargs": {},
99
+ "train_freq": {
100
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
101
+ ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
102
+ },
103
+ "use_sde_at_warmup": false,
104
+ "exploration_initial_eps": 1.0,
105
+ "exploration_final_eps": 0.05,
106
+ "exploration_fraction": 0.1,
107
+ "target_update_interval": 625,
108
+ "_n_calls": 62500,
109
+ "max_grad_norm": 10,
110
+ "exploration_rate": 0.05,
111
+ "lr_schedule": {
112
+ ":type:": "<class 'function'>",
113
+ ":serialized:": "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"
114
+ },
115
+ "batch_norm_stats": [],
116
+ "batch_norm_stats_target": [],
117
+ "exploration_schedule": {
118
+ ":type:": "<class 'function'>",
119
+ ":serialized:": "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"
120
+ }
121
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9da39328f27f1627645e795ed42de873da5ac71bd09e62b6ce312090cbdd78c3
3
+ size 45344
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:03cf1bf42b1193ebfb449a632734249d3eb8c89a3062b776aa8e88ed479fff05
3
+ size 44466
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.2.1+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.25.2
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (194 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -46.67593634636141, "std_reward": 49.682424436822394, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-08T10:27:32.738400"}