Upload PPO LunarLander-v2 trained agent
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: 267.95 +/- 20.49
|
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 0x7e1459251870>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e1459251900>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e1459251990>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e1459251a20>", "_build": "<function ActorCriticPolicy._build at 0x7e1459251ab0>", "forward": "<function ActorCriticPolicy.forward at 0x7e1459251b40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e1459251bd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e1459251c60>", "_predict": "<function ActorCriticPolicy._predict at 0x7e1459251cf0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e1459251d80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e1459251e10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e1459251ea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e1459258700>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708973173050842264, "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": 347, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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": "2.1.0+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:d28ca64e3447e15b7356c9f403d23716c6cb38962f69f68adc79e7acdb895a36
|
3 |
+
size 147983
|
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 0x7e1459251870>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e1459251900>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e1459251990>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e1459251a20>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7e1459251ab0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7e1459251b40>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7e1459251bd0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e1459251c60>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7e1459251cf0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e1459251d80>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e1459251e10>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7e1459251ea0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7e1459258700>"
|
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": 1708973173050842264,
|
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": 347,
|
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": 2048,
|
81 |
+
"gamma": 0.99,
|
82 |
+
"gae_lambda": 0.95,
|
83 |
+
"ent_coef": 0.0,
|
84 |
+
"vf_coef": 0.5,
|
85 |
+
"max_grad_norm": 0.5,
|
86 |
+
"batch_size": 64,
|
87 |
+
"n_epochs": 10,
|
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 sha256:1e031ee623f91a8148f305b706e51bc9e22664cd34939fb7e43884fe863c4b17
|
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:c9c9a8f4d48d0e089d38cbd07d48d041674f8d04ea2449a2a55a6c0568c516d1
|
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: 2.1.0+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 (182 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 267.9470255246051, "std_reward": 20.485444520641625, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-26T19:24:17.188060"}
|