Jhin4 commited on
Commit
48c662e
1 Parent(s): 1caa26d

Upload DQN LunarLander-v2 trained agent

Browse files
DQN-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:11a2241679204a1150543a79d86a5960ab10b5f921aee1a5b760a0d100c9bef1
3
+ size 1133762
DQN-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
DQN-LunarLander-v2/data ADDED
@@ -0,0 +1,126 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7f15a805ecb0>",
9
+ "_build": "<function DQNPolicy._build at 0x7f15a805ed40>",
10
+ "make_q_net": "<function DQNPolicy.make_q_net at 0x7f15a805edd0>",
11
+ "forward": "<function DQNPolicy.forward at 0x7f15a805ee60>",
12
+ "_predict": "<function DQNPolicy._predict at 0x7f15a805eef0>",
13
+ "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f15a805ef80>",
14
+ "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f15a805f010>",
15
+ "__abstractmethods__": "frozenset()",
16
+ "_abc_impl": "<_abc._abc_data object at 0x7f15a8070b40>"
17
+ },
18
+ "verbose": 1,
19
+ "policy_kwargs": {
20
+ "net_arch": [
21
+ 256,
22
+ 256
23
+ ]
24
+ },
25
+ "num_timesteps": 1000000,
26
+ "_total_timesteps": 1000000,
27
+ "_num_timesteps_at_start": 0,
28
+ "seed": null,
29
+ "action_noise": null,
30
+ "start_time": 1702384689341971388,
31
+ "learning_rate": 0.0001,
32
+ "tensorboard_log": null,
33
+ "_last_obs": {
34
+ ":type:": "<class 'numpy.ndarray'>",
35
+ ":serialized:": "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"
36
+ },
37
+ "_last_episode_starts": {
38
+ ":type:": "<class 'numpy.ndarray'>",
39
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
40
+ },
41
+ "_last_original_obs": {
42
+ ":type:": "<class 'numpy.ndarray'>",
43
+ ":serialized:": "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"
44
+ },
45
+ "_episode_num": 2122,
46
+ "use_sde": false,
47
+ "sde_sample_freq": -1,
48
+ "_current_progress_remaining": 0.0,
49
+ "_stats_window_size": 100,
50
+ "ep_info_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "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"
53
+ },
54
+ "ep_success_buffer": {
55
+ ":type:": "<class 'collections.deque'>",
56
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
57
+ },
58
+ "_n_updates": 178125,
59
+ "observation_space": {
60
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
61
+ ":serialized:": "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",
62
+ "dtype": "float32",
63
+ "bounded_below": "[ True True True True True True True True]",
64
+ "bounded_above": "[ True True True True True True True True]",
65
+ "_shape": [
66
+ 8
67
+ ],
68
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
69
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
70
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
71
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
72
+ "_np_random": null
73
+ },
74
+ "action_space": {
75
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
76
+ ":serialized:": "gAWVgAEAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlIwUbnVtcHkucmFuZG9tLl9waWNrbGWUjBBfX2dlbmVyYXRvcl9jdG9ylJOUjAVQQ0c2NJSFlFKUfZQojA1iaXRfZ2VuZXJhdG9ylIwFUENHNjSUjAVzdGF0ZZR9lChoI4oQ0yavcW2bpdiUKfjT4cP5dIwDaW5jlIoQs79OXebN+7t7V4CdGK4bMXWMCmhhc191aW50MzKUSwCMCHVpbnRlZ2VylEo9ergSdWJ1Yi4=",
77
+ "n": "4",
78
+ "start": "0",
79
+ "_shape": [],
80
+ "dtype": "int64",
81
+ "_np_random": "Generator(PCG64)"
82
+ },
83
+ "n_envs": 16,
84
+ "buffer_size": 100000,
85
+ "batch_size": 128,
86
+ "learning_starts": 50000,
87
+ "tau": 1.0,
88
+ "gamma": 0.99,
89
+ "gradient_steps": 3,
90
+ "optimize_memory_usage": false,
91
+ "replay_buffer_class": {
92
+ ":type:": "<class 'abc.ABCMeta'>",
93
+ ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
94
+ "__module__": "stable_baselines3.common.buffers",
95
+ "__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 ",
96
+ "__init__": "<function ReplayBuffer.__init__ at 0x7f15a8043130>",
97
+ "add": "<function ReplayBuffer.add at 0x7f15a80431c0>",
98
+ "sample": "<function ReplayBuffer.sample at 0x7f15a8043250>",
99
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7f15a80432e0>",
100
+ "__abstractmethods__": "frozenset()",
101
+ "_abc_impl": "<_abc._abc_data object at 0x7f15a803fc00>"
102
+ },
103
+ "replay_buffer_kwargs": {},
104
+ "train_freq": {
105
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
106
+ ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
107
+ },
108
+ "use_sde_at_warmup": false,
109
+ "exploration_initial_eps": 1.0,
110
+ "exploration_final_eps": 0.05,
111
+ "exploration_fraction": 0.1,
112
+ "target_update_interval": 625,
113
+ "_n_calls": 62500,
114
+ "max_grad_norm": 10,
115
+ "exploration_rate": 0.05,
116
+ "lr_schedule": {
117
+ ":type:": "<class 'function'>",
118
+ ":serialized:": "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"
119
+ },
120
+ "batch_norm_stats": [],
121
+ "batch_norm_stats_target": [],
122
+ "exploration_schedule": {
123
+ ":type:": "<class 'function'>",
124
+ ":serialized:": "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"
125
+ }
126
+ }
DQN-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e0a7631a57c60a71615c6c34942065aaac8b0942c2d74a3ef57bb2083b19e974
3
+ size 558240
DQN-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1ca5bb5b86ee77a6c90858eabb4369984337fdccb6650d99ed1004673adb30af
3
+ size 557362
DQN-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
DQN-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu118
5
+ - GPU Enabled: False
6
+ - Numpy: 1.23.5
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
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: DQN
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: 241.60 +/- 48.03
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **DQN** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **DQN** 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 0x7f15a805ecb0>", "_build": "<function DQNPolicy._build at 0x7f15a805ed40>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7f15a805edd0>", "forward": "<function DQNPolicy.forward at 0x7f15a805ee60>", "_predict": "<function DQNPolicy._predict at 0x7f15a805eef0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f15a805ef80>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f15a805f010>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f15a8070b40>"}, "verbose": 1, "policy_kwargs": {"net_arch": [256, 256]}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1702384689341971388, "learning_rate": 0.0001, "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": 2122, "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": 178125, "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": 100000, "batch_size": 128, "learning_starts": 50000, "tau": 1.0, "gamma": 0.99, "gradient_steps": 3, "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 0x7f15a8043130>", "add": "<function ReplayBuffer.add at 0x7f15a80431c0>", "sample": "<function ReplayBuffer.sample at 0x7f15a8043250>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7f15a80432e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f15a803fc00>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
replay.mp4 ADDED
Binary file (125 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 241.5976393, "std_reward": 48.034285487523235, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-12T13:12:03.944541"}