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: -3.98 +/- 109.69
|
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 0x7f6151284af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6151284b80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6151284c10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6151284ca0>", "_build": "<function ActorCriticPolicy._build at 0x7f6151284d30>", "forward": "<function ActorCriticPolicy.forward at 0x7f6151284dc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6151284e50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6151284ee0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6151284f70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6151285000>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6151285090>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6151285120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f6151280880>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 81920, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713616928103246283, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADPp0jyGqbQ/Zmy7PvRsQb38JPS8tdddvQAAAAAAAAAAAFBGPLK4sT92YB4/tS4DvyW2grwRWTi+AAAAAAAAAAAT+wE+Js07P+bGPz6/+Gm/iICFPZ2cs70AAAAAAAAAAPr/Ej7uxBc/rUGoPjyPhr8SNUG81riovQAAAAAAAAAAJhvdvQJarz9yg1m+vtXtvrlVLD6qXxw8AAAAAAAAAACaVxa+srmvPwxZCb888pS+qPsGPv7vhz0AAAAAAAAAAA2e0r20qK8/+MInv/tHIL45ylk9uiNKPQAAAAAAAAAAmpmXvK94mT8GO8G9Wr4Bv/fXmrzu6dS9AAAAAAAAAAAmRA++DMCyP1ekqb5UNo++GBoWvWYTP74AAAAAAAAAAOA4GL6uH8M/QwM7vwWoRj22O5c9mtrMvAAAAAAAAAAANqFWvlzerz81tWK/nCo7vtqzGj7J6yU+AAAAAAAAAABYPKG+l6x0Pws7Dr+l5U2/IGztvPIMqT0AAAAAAAAAADOjsTs9qqw/+BfdPXaVGr9f8wC85mS9vAAAAAAAAAAA4AsOvnuwJj8E9aa+VbOLvwW5jD36pw+9AAAAAAAAAADzJUG+ShaQP2C7Bb+SEEW/vFFbPZ6BOb4AAAAAAAAAAJpJ8btoNbE/baSavW/sFL6Wns484fIgPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": 0.91808, "_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": 16, "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 sha256:691845a47220f1b541897d0c1c5ee7cb9e4717050477bc47409ea37e86c27791
|
3 |
+
size 147935
|
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 0x7f6151284af0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6151284b80>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6151284c10>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6151284ca0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f6151284d30>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f6151284dc0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6151284e50>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6151284ee0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f6151284f70>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6151285000>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6151285090>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6151285120>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f6151280880>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 81920,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1713616928103246283,
|
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": 0.91808,
|
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": 16,
|
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 sha256:58f52424990763f4a9310ac2d0c09c26169e33c421833e5788d4f8ab56a0dd0f
|
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:ec2402f98ac50e49223277c49a1144dbcd80002f2475da24d353b662e2c3054e
|
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 (197 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -3.977992699999997, "std_reward": 109.68696260405727, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-20T12:46:54.114230"}
|