nikitakapitan commited on
Commit
5037f54
1 Parent(s): d367d2b

Initial commit: upload trained PPO LunarLander-v2

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 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: -133.00 +/- 26.78
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**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
26
+
27
+ ## Usage (with Stable-baselines3)
28
+ TODO: Add your code
29
+
30
+
31
+ ```python
32
+ from stable_baselines3 import ...
33
+ from huggingface_sb3 import load_from_hub
34
+
35
+ ...
36
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f596b7a17a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f596b7a1830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f596b7a18c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f596b7a1950>", "_build": "<function ActorCriticPolicy._build at 0x7f596b7a19e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f596b7a1a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f596b7a1b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7f596b7a1b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f596b7a1c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f596b7a1cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f596b7a1d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f596b7eba50>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "num_timesteps": 1001472, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1654686590.2432485, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVqgAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLCIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMgvt7IvuSblT9aDQC+M+4sO6mNRbwqCyU8AAAAAAAAAACUdJRiLg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQCUdJRiLg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0014719999999999178, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1956, "n_steps": 2048, "gamma": 0.9, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gASVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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 sha256:859694b662cc9edc60d6e420d2db473764f0ab00088b5473e9683557cf538b42
3
+ size 143448
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:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
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 0x7f596b7a17a0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f596b7a1830>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f596b7a18c0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f596b7a1950>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f596b7a19e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f596b7a1a70>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f596b7a1b00>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f596b7a1b90>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f596b7a1c20>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f596b7a1cb0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f596b7a1d40>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f596b7eba50>"
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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 1,
45
+ "num_timesteps": 1001472,
46
+ "_total_timesteps": 1000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1654686590.2432485,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "gASVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "gASVqgAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLCIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMgvt7IvuSblT9aDQC+M+4sO6mNRbwqCyU8AAAAAAAAAACUdJRiLg=="
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQCUdJRiLg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.0014719999999999178,
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 1956,
79
+ "n_steps": 2048,
80
+ "gamma": 0.9,
81
+ "gae_lambda": 0.95,
82
+ "ent_coef": 0.0,
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:cefa1f93c41bc2dd2ab24742c24fd64049fc2cf9c627c057a671ecf102135829
3
+ size 84829
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:32ecaac5b2580e9e871f7ab23c54785538413840449c044d77889dcb5ab225b1
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:d87a85d13942ff9d0ffcf78098c727496eb790ea38ed4e4e5264006c9d15aad3
3
+ size 227143
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -132.99973513274236, "std_reward": 26.776298969773688, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-08T11:52:34.719072"}