agercas commited on
Commit
bf1668a
1 Parent(s): d53613d

Upload DQN MountainCar agent trained for 10M steps with default hyperparameters

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - MountainCar-v0
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: MountainCar-v0
16
+ type: MountainCar-v0
17
+ metrics:
18
+ - type: mean_reward
19
+ value: -116.60 +/- 27.47
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **DQN** Agent playing **MountainCar-v0**
25
+ This is a trained model of a **DQN** agent playing **MountainCar-v0**
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", "__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 0x15aa541f0>", "_build": "<function DQNPolicy._build at 0x15aa54280>", "make_q_net": "<function DQNPolicy.make_q_net at 0x15aa54310>", "forward": "<function DQNPolicy.forward at 0x15aa543a0>", "_predict": "<function DQNPolicy._predict at 0x15aa54430>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x15aa544c0>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x15aa54550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x15aa57180>"}, "verbose": 0, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVYwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLAoWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAACamZm/KVyPvZRoCksChZSMAUOUdJRSlIwEaGlnaJRoEiiWCAAAAAAAAACamRk/KVyPPZRoCksChZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolgIAAAAAAAAAAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAoWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYCAAAAAAAAAAEBlGghSwKFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "_shape": [2], "low": "[-1.2 -0.07]", "high": "[0.6 0.07]", "bounded_below": "[ True True]", "bounded_above": "[ True True]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "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", "n": 3, "_shape": [], "dtype": "int64", "_np_random": "RandomState(MT19937)"}, "n_envs": 1, "num_timesteps": 10000000, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677536567915886000, "learning_rate": 0.0001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAANvgw753sGQ8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwKGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAF8Gy740i2M8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwKGlIwBQ5R0lFKULg=="}, "_episode_num": 70716, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 2487500, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 50000, "tau": 1.0, "gamma": 0.99, "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 0x15aa21940>", "add": "<function ReplayBuffer.add at 0x15aa219d0>", "sample": "<function ReplayBuffer.sample at 0x15aa21a60>", "_get_samples": "<function ReplayBuffer._get_samples at 0x15aa21af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x15aa29e40>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "actor": null, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 10000, "_n_calls": 10000000, "max_grad_norm": 10, "exploration_rate": 0.05, "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "system_info": {"OS": "macOS-13.2.1-arm64-arm-64bit Darwin Kernel Version 22.3.0: Mon Jan 30 20:39:35 PST 2023; root:xnu-8792.81.3~2/RELEASE_ARM64_T8103", "Python": "3.9.7", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1", "GPU Enabled": "False", "Numpy": "1.23.5", "Gym": "0.21.0"}}
dqn-MountainCar-v0.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:770f014c103922d92d1155c724bd217984026ff98b72210e24096bb76f1a0335
3
+ size 100191
dqn-MountainCar-v0/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
dqn-MountainCar-v0/data ADDED
@@ -0,0 +1,117 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.dqn.policies",
6
+ "__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 ",
7
+ "__init__": "<function DQNPolicy.__init__ at 0x15aa541f0>",
8
+ "_build": "<function DQNPolicy._build at 0x15aa54280>",
9
+ "make_q_net": "<function DQNPolicy.make_q_net at 0x15aa54310>",
10
+ "forward": "<function DQNPolicy.forward at 0x15aa543a0>",
11
+ "_predict": "<function DQNPolicy._predict at 0x15aa54430>",
12
+ "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x15aa544c0>",
13
+ "set_training_mode": "<function DQNPolicy.set_training_mode at 0x15aa54550>",
14
+ "__abstractmethods__": "frozenset()",
15
+ "_abc_impl": "<_abc._abc_data object at 0x15aa57180>"
16
+ },
17
+ "verbose": 0,
18
+ "policy_kwargs": {},
19
+ "observation_space": {
20
+ ":type:": "<class 'gym.spaces.box.Box'>",
21
+ ":serialized:": "gAWVYwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLAoWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAACamZm/KVyPvZRoCksChZSMAUOUdJRSlIwEaGlnaJRoEiiWCAAAAAAAAACamRk/KVyPPZRoCksChZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolgIAAAAAAAAAAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAoWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYCAAAAAAAAAAEBlGghSwKFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
22
+ "dtype": "float32",
23
+ "_shape": [
24
+ 2
25
+ ],
26
+ "low": "[-1.2 -0.07]",
27
+ "high": "[0.6 0.07]",
28
+ "bounded_below": "[ True True]",
29
+ "bounded_above": "[ True True]",
30
+ "_np_random": null
31
+ },
32
+ "action_space": {
33
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
34
+ ":serialized:": "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",
35
+ "n": 3,
36
+ "_shape": [],
37
+ "dtype": "int64",
38
+ "_np_random": "RandomState(MT19937)"
39
+ },
40
+ "n_envs": 1,
41
+ "num_timesteps": 10000000,
42
+ "_total_timesteps": 10000000,
43
+ "_num_timesteps_at_start": 0,
44
+ "seed": null,
45
+ "action_noise": null,
46
+ "start_time": 1677536567915886000,
47
+ "learning_rate": 0.0001,
48
+ "tensorboard_log": null,
49
+ "lr_schedule": {
50
+ ":type:": "<class 'function'>",
51
+ ":serialized:": "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"
52
+ },
53
+ "_last_obs": {
54
+ ":type:": "<class 'numpy.ndarray'>",
55
+ ":serialized:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAANvgw753sGQ8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwKGlIwBQ5R0lFKULg=="
56
+ },
57
+ "_last_episode_starts": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
60
+ },
61
+ "_last_original_obs": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAF8Gy740i2M8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwKGlIwBQ5R0lFKULg=="
64
+ },
65
+ "_episode_num": 70716,
66
+ "use_sde": false,
67
+ "sde_sample_freq": -1,
68
+ "_current_progress_remaining": 0.0,
69
+ "ep_info_buffer": {
70
+ ":type:": "<class 'collections.deque'>",
71
+ ":serialized:": "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"
72
+ },
73
+ "ep_success_buffer": {
74
+ ":type:": "<class 'collections.deque'>",
75
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
76
+ },
77
+ "_n_updates": 2487500,
78
+ "buffer_size": 1000000,
79
+ "batch_size": 32,
80
+ "learning_starts": 50000,
81
+ "tau": 1.0,
82
+ "gamma": 0.99,
83
+ "gradient_steps": 1,
84
+ "optimize_memory_usage": false,
85
+ "replay_buffer_class": {
86
+ ":type:": "<class 'abc.ABCMeta'>",
87
+ ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
88
+ "__module__": "stable_baselines3.common.buffers",
89
+ "__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 ",
90
+ "__init__": "<function ReplayBuffer.__init__ at 0x15aa21940>",
91
+ "add": "<function ReplayBuffer.add at 0x15aa219d0>",
92
+ "sample": "<function ReplayBuffer.sample at 0x15aa21a60>",
93
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x15aa21af0>",
94
+ "__abstractmethods__": "frozenset()",
95
+ "_abc_impl": "<_abc._abc_data object at 0x15aa29e40>"
96
+ },
97
+ "replay_buffer_kwargs": {},
98
+ "train_freq": {
99
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
100
+ ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
101
+ },
102
+ "actor": null,
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": 10000,
108
+ "_n_calls": 10000000,
109
+ "max_grad_norm": 10,
110
+ "exploration_rate": 0.05,
111
+ "exploration_schedule": {
112
+ ":type:": "<class 'function'>",
113
+ ":serialized:": "gAWVsQMAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLBEsTQyxkAXwAGACIAWsEchCIAFMAiAJkAXwAGACIAIgCGAAUAIgBGwAXAFMAZABTAJROSwGGlCmMEnByb2dyZXNzX3JlbWFpbmluZ5SFlIxtL1VzZXJzL2FnZXJjYXMvLnB5ZW52L3ZlcnNpb25zLzMuOS43L2VudnMvcWhhY2svbGliL3B5dGhvbjMuOS9zaXRlLXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS3BDBgABDAEEApSMA2VuZJSMDGVuZF9mcmFjdGlvbpSMBXN0YXJ0lIeUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMbS9Vc2Vycy9hZ2VyY2FzLy5weWVudi92ZXJzaW9ucy8zLjkuNy9lbnZzL3FoYWNrL2xpYi9weXRob24zLjkvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpRoHSlSlGgdKVKUh5R0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCN9lH2UKGgYaA2MDF9fcXVhbG5hbWVfX5SMG2dldF9saW5lYXJfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lChoCowIYnVpbHRpbnOUjAVmbG9hdJSTlIwGcmV0dXJulGgvdYwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP6mZmZmZmZqFlFKUaDdHP7mZmZmZmZqFlFKUaDdHP/AAAAAAAACFlFKUh5SMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
114
+ },
115
+ "batch_norm_stats": [],
116
+ "batch_norm_stats_target": []
117
+ }
dqn-MountainCar-v0/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:67917715fca5d74d2ef4d56ad2bfcbc5e2c7fb6a13fe39dea22ec31d70675a60
3
+ size 41199
dqn-MountainCar-v0/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:610489a834641f05114ef6de5a9f99161a6258ffac239f1bde67d5039f5099e9
3
+ size 40321
dqn-MountainCar-v0/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
dqn-MountainCar-v0/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: macOS-13.2.1-arm64-arm-64bit Darwin Kernel Version 22.3.0: Mon Jan 30 20:39:35 PST 2023; root:xnu-8792.81.3~2/RELEASE_ARM64_T8103
2
+ - Python: 3.9.7
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1
5
+ - GPU Enabled: False
6
+ - Numpy: 1.23.5
7
+ - Gym: 0.21.0
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -116.6, "std_reward": 27.46707119443207, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-28T00:34:19.405854"}