Commit
•
bfda4a9
1
Parent(s):
658c421
First attempt at Lunar Lander for RL course
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +99 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +9 -0
- replay.mp4 +0 -0
- results.json +1 -0
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: 218.20 +/- 49.94
|
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:": "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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7a03b519b250>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a03b519b2e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a03b519b370>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a03b519b400>", "_build": "<function ActorCriticPolicy._build at 0x7a03b519b490>", "forward": "<function ActorCriticPolicy.forward at 0x7a03b519b520>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a03b519b5b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a03b519b640>", "_predict": "<function ActorCriticPolicy._predict at 0x7a03b519b6d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a03b519b760>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a03b519b7f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a03b519b880>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a03c292a980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1702073355069302999, "learning_rate": 0.00025, "tensorboard_log": null, "_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": -0.015808000000000044, "_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": 465, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.005, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 15, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_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": "True", "Numpy": "1.23.5", "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:de3a75b8b34b5da1631cfb0178598868d4542773915926bb313159793ac80ce2
|
3 |
+
size 147993
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7a03b519b250>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a03b519b2e0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a03b519b370>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a03b519b400>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7a03b519b490>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7a03b519b520>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7a03b519b5b0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a03b519b640>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7a03b519b6d0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a03b519b760>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a03b519b7f0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7a03b519b880>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7a03c292a980>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1702073355069302999,
|
30 |
+
"learning_rate": 0.00025,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"_last_obs": {
|
33 |
+
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "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"
|
35 |
+
},
|
36 |
+
"_last_episode_starts": {
|
37 |
+
":type:": "<class 'numpy.ndarray'>",
|
38 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -0.015808000000000044,
|
45 |
+
"_stats_window_size": 100,
|
46 |
+
"ep_info_buffer": {
|
47 |
+
":type:": "<class 'collections.deque'>",
|
48 |
+
":serialized:": "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"
|
49 |
+
},
|
50 |
+
"ep_success_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
+
},
|
54 |
+
"_n_updates": 465,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
80 |
+
"n_steps": 2048,
|
81 |
+
"gamma": 0.99,
|
82 |
+
"gae_lambda": 0.95,
|
83 |
+
"ent_coef": 0.005,
|
84 |
+
"vf_coef": 0.5,
|
85 |
+
"max_grad_norm": 0.5,
|
86 |
+
"batch_size": 128,
|
87 |
+
"n_epochs": 15,
|
88 |
+
"clip_range": {
|
89 |
+
":type:": "<class 'function'>",
|
90 |
+
":serialized:": "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"
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null,
|
95 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
+
}
|
99 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5c965d849b150721019083bda4090f4058e194be4f05d54e484b63652066fc30
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:92544c58f342304d358f912bc6d1b7b8b2659c728399a08a22288df58d5e2ca9
|
3 |
+
size 43762
|
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-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: True
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (131 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 218.2002131, "std_reward": 49.939013269825104, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-08T22:36:19.876434"}
|