Commit
·
460698a
1
Parent(s):
4a09d66
Upload the trained agent for LundarLander-v2
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: 252.38 +/- 20.26
|
| 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 0x7a298a0fbe20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a298a0fbeb0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a298a0fbf40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a298a108040>", "_build": "<function ActorCriticPolicy._build at 0x7a298a1080d0>", "forward": "<function ActorCriticPolicy.forward at 0x7a298a108160>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a298a1081f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a298a108280>", "_predict": "<function ActorCriticPolicy._predict at 0x7a298a108310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a298a1083a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a298a108430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a298a1084c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a298a0e8fc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714477169066932765, "learning_rate": 0.0003, "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": 248, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "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-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 sha256:6dde7417f3133fc54fc2ae58dcb55596b47376d85aa27c52b176a68808225a93
|
| 3 |
+
size 148088
|
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 0x7a298a0fbe20>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a298a0fbeb0>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a298a0fbf40>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a298a108040>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7a298a1080d0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7a298a108160>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7a298a1081f0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a298a108280>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7a298a108310>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a298a1083a0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a298a108430>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7a298a1084c0>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7a298a0e8fc0>"
|
| 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": 1714477169066932765,
|
| 30 |
+
"learning_rate": 0.0003,
|
| 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": 248,
|
| 55 |
+
"observation_space": {
|
| 56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
| 57 |
+
":serialized:": "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",
|
| 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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
| 73 |
+
"n": "4",
|
| 74 |
+
"start": "0",
|
| 75 |
+
"_shape": [],
|
| 76 |
+
"dtype": "int64",
|
| 77 |
+
"_np_random": null
|
| 78 |
+
},
|
| 79 |
+
"n_envs": 16,
|
| 80 |
+
"n_steps": 1024,
|
| 81 |
+
"gamma": 0.999,
|
| 82 |
+
"gae_lambda": 0.98,
|
| 83 |
+
"ent_coef": 0.01,
|
| 84 |
+
"vf_coef": 0.5,
|
| 85 |
+
"max_grad_norm": 0.5,
|
| 86 |
+
"batch_size": 64,
|
| 87 |
+
"n_epochs": 4,
|
| 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:eb27b52362521e81e1b59821daf0bdbc6d182871667eb8ff60106a0a129913d9
|
| 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:d7296483697bacc5fa62f65ab899e789e9941c922a32718f1953495731aaf3aa
|
| 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-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 (193 kB). View file
|
|
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 252.38002179999998, "std_reward": 20.261361416634333, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-30T12:02:34.924972"}
|