Clément Thiriet
commited on
Commit
•
a7cce4b
1
Parent(s):
de09537
First LunarLander-v2 PPO model
Browse files- LunarLander-v2.zip +3 -0
- LunarLander-v2/_stable_baselines3_version +1 -0
- LunarLander-v2/data +95 -0
- LunarLander-v2/policy.optimizer.pth +3 -0
- LunarLander-v2/policy.pth +3 -0
- LunarLander-v2/pytorch_variables.pth +3 -0
- LunarLander-v2/system_info.txt +7 -0
- README.md +37 -0
- config.json +1 -0
- replay.mp4 +0 -0
- results.json +1 -0
LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b7f9d81f8b4ff500b086cbd58dabae8fb71a4b3e8c69b682902078bb4d34950d
|
3 |
+
size 147424
|
LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
LunarLander-v2/data
ADDED
@@ -0,0 +1,95 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f95c1d114c0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f95c1d11550>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f95c1d115e0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f95c1d11670>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f95c1d11700>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f95c1d11790>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f95c1d11820>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f95c1d118b0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f95c1d11940>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f95c1d119d0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f95c1d11a60>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f95c1d11af0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7f95c1d0b930>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"dtype": "float32",
|
28 |
+
"_shape": [
|
29 |
+
8
|
30 |
+
],
|
31 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
32 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
33 |
+
"bounded_below": "[False False False False False False False False]",
|
34 |
+
"bounded_above": "[False False False False False False False False]",
|
35 |
+
"_np_random": null
|
36 |
+
},
|
37 |
+
"action_space": {
|
38 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
39 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
40 |
+
"n": 4,
|
41 |
+
"_shape": [],
|
42 |
+
"dtype": "int64",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 16,
|
46 |
+
"num_timesteps": 1015808,
|
47 |
+
"_total_timesteps": 1000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1676828054281141796,
|
52 |
+
"learning_rate": 0.0003,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'numpy.ndarray'>",
|
60 |
+
":serialized:": "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"
|
61 |
+
},
|
62 |
+
"_last_episode_starts": {
|
63 |
+
":type:": "<class 'numpy.ndarray'>",
|
64 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
65 |
+
},
|
66 |
+
"_last_original_obs": null,
|
67 |
+
"_episode_num": 0,
|
68 |
+
"use_sde": false,
|
69 |
+
"sde_sample_freq": -1,
|
70 |
+
"_current_progress_remaining": -0.015808000000000044,
|
71 |
+
"ep_info_buffer": {
|
72 |
+
":type:": "<class 'collections.deque'>",
|
73 |
+
":serialized:": "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"
|
74 |
+
},
|
75 |
+
"ep_success_buffer": {
|
76 |
+
":type:": "<class 'collections.deque'>",
|
77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
78 |
+
},
|
79 |
+
"_n_updates": 248,
|
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 |
+
}
|
LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:bd24a28f1168008d4c0db912283dfd768cd7227468e52d994df22f7e3c8fa95e
|
3 |
+
size 87929
|
LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:403d3c9bfc241a331f5fe640498c59e7992f2540592457c8b6fa955623ad1927
|
3 |
+
size 43393
|
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
|
LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.8.10
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.21.6
|
7 |
+
- Gym: 0.21.0
|
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: 249.07 +/- 23.84
|
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 0x7f95c1d114c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f95c1d11550>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f95c1d115e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f95c1d11670>", "_build": "<function ActorCriticPolicy._build at 0x7f95c1d11700>", "forward": "<function ActorCriticPolicy.forward at 0x7f95c1d11790>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f95c1d11820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f95c1d118b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f95c1d11940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f95c1d119d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f95c1d11a60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f95c1d11af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f95c1d0b930>"}, "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:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676828054281141796, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVfxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIzEI7p9l+Z0CUhpRSlIwBbJRN6AOMAXSUR0CT5bZFocrBdX2UKGgGaAloD0MIt7WF56WNYECUhpRSlGgVTegDaBZHQJPmMR15jYt1fZQoaAZoCWgPQwjkvP+Pk+pjQJSGlFKUaBVN6ANoFkdAk+5v6TGHYnV9lChoBmgJaA9DCPol4q3zmWVAlIaUUpRoFU3oA2gWR0CT7yMfigkDdX2UKGgGaAloD0MIfjfdssOEZkCUhpRSlGgVTegDaBZHQJP3VO+IuXh1fZQoaAZoCWgPQwgiGt1BbGxkQJSGlFKUaBVN6ANoFkdAk/911B+nZXV9lChoBmgJaA9DCK+0jNR7/1pAlIaUUpRoFU3oA2gWR0CUAjWSlnAZdX2UKGgGaAloD0MIXRYTm48TZUCUhpRSlGgVTegDaBZHQJQMPB/I8yN1fZQoaAZoCWgPQwipo+NqZDdmQJSGlFKUaBVN6ANoFkdAlA/wxSHdoHV9lChoBmgJaA9DCBsS91j6cl9AlIaUUpRoFU3oA2gWR0CUFU6Kcd5qdX2UKGgGaAloD0MIXg8mxcdNXUCUhpRSlGgVTegDaBZHQJQWDWK/Efl1fZQoaAZoCWgPQwioNGJmn7VjQJSGlFKUaBVN6ANoFkdAlBgWHk92YHV9lChoBmgJaA9DCMGRQINNoWFAlIaUUpRoFU3oA2gWR0CUHN5H3DekdX2UKGgGaAloD0MIbjE/N7QcY0CUhpRSlGgVTegDaBZHQJQ8ZFRYRul1fZQoaAZoCWgPQwgNNQpJZoNiQJSGlFKUaBVN6ANoFkdAlENlx4ptrXV9lChoBmgJaA9DCAx5BDfS/WBAlIaUUpRoFU3oA2gWR0CUSC/r0J4TdX2UKGgGaAloD0MIBeCfUqXfY0CUhpRSlGgVTegDaBZHQJRMyVE/jbV1fZQoaAZoCWgPQwhkIqXZPNlhQJSGlFKUaBVN6ANoFkdAlE0jwMH8j3V9lChoBmgJaA9DCNeIYBxcOGRAlIaUUpRoFU3oA2gWR0CUUtFB6a9cdX2UKGgGaAloD0MIKNTTR+BcZECUhpRSlGgVTegDaBZHQJRTZa/yoXN1fZQoaAZoCWgPQwjb2y3JAY8wQJSGlFKUaBVNEAFoFkdAlFhTIeYD1XV9lChoBmgJaA9DCF4QkZp2aWNAlIaUUpRoFU3oA2gWR0CUXj4uK4x2dX2UKGgGaAloD0MIrOKNzCNUY0CUhpRSlGgVTegDaBZHQJRoZmvnr6d1fZQoaAZoCWgPQwhjRKLQMhphQJSGlFKUaBVN6ANoFkdAlGrq5CngpHV9lChoBmgJaA9DCDuMSX+vNGdAlIaUUpRoFU3oA2gWR0CUdBk/8l5XdX2UKGgGaAloD0MICme3lsl8YkCUhpRSlGgVTegDaBZHQJR3nldTo+x1fZQoaAZoCWgPQwjlt+hkKZljQJSGlFKUaBVN6ANoFkdAlHzibx3FDXV9lChoBmgJaA9DCBnlmZdDd2NAlIaUUpRoFU3oA2gWR0CUfZJHAh0RdX2UKGgGaAloD0MIfxZLkXy2YkCUhpRSlGgVTegDaBZHQJR/HDhtLth1fZQoaAZoCWgPQwjHuyNjtdNhQJSGlFKUaBVN6ANoFkdAlIHu6Zpi7XV9lChoBmgJaA9DCPm9TX/2xF1AlIaUUpRoFU3oA2gWR0CUn4876pHadX2UKGgGaAloD0MI/N8RFarrE0CUhpRSlGgVTQkBaBZHQJSn3qZ+hGp1fZQoaAZoCWgPQwgoC19fa1JkQJSGlFKUaBVN6ANoFkdAlKlukP+XJHV9lChoBmgJaA9DCOp4zEBl4mJAlIaUUpRoFU3oA2gWR0CUrRPTXrdFdX2UKGgGaAloD0MIsd8T69TnYkCUhpRSlGgVTegDaBZHQJStY6ltTDR1fZQoaAZoCWgPQwiWsDbGzn5kQJSGlFKUaBVN6ANoFkdAlLJHfyf+THV9lChoBmgJaA9DCNmyfF0G2WJAlIaUUpRoFU3oA2gWR0CUsrQeFL39dX2UKGgGaAloD0MIntMs0G7yZUCUhpRSlGgVTegDaBZHQJS1s1aW5Yp1fZQoaAZoCWgPQwiw5gDBHJVhQJSGlFKUaBVN6ANoFkdAlLlMGHHmzXV9lChoBmgJaA9DCG9JDtjVxFpAlIaUUpRoFU3oA2gWR0CUwALxI8QqdX2UKGgGaAloD0MIjzUjg9x5XkCUhpRSlGgVTegDaBZHQJTCUBU70Wd1fZQoaAZoCWgPQwhyFva0Q/1jQJSGlFKUaBVN6ANoFkdAlMvxxYJVsHV9lChoBmgJaA9DCN+j/nqFo2BAlIaUUpRoFU3oA2gWR0CU0LIt16mgdX2UKGgGaAloD0MICwkYXd46Y0CUhpRSlGgVTegDaBZHQJTXYVwgkkd1fZQoaAZoCWgPQwgaGHlZk4RkQJSGlFKUaBVN6ANoFkdAlNhN8ma6SXV9lChoBmgJaA9DCHlZEwt8D2RAlIaUUpRoFU3oA2gWR0CU3nKYAsCldX2UKGgGaAloD0MIKm9HOK2cY0CUhpRSlGgVTegDaBZHQJT31II4VAR1fZQoaAZoCWgPQwi536Eo0ItKQJSGlFKUaBVNAgFoFkdAlP3KRyOrAHV9lChoBmgJaA9DCO4kIvwLn2NAlIaUUpRoFU3oA2gWR0CVAML0jC53dX2UKGgGaAloD0MI2xMktrsUXkCUhpRSlGgVTegDaBZHQJUCfeIl+mZ1fZQoaAZoCWgPQwgIAmTo2IFhQJSGlFKUaBVN6ANoFkdAlQbhciW3SnV9lChoBmgJaA9DCFoO9FDbjV1AlIaUUpRoFU3oA2gWR0CVB2/Pw/gSdX2UKGgGaAloD0MIjPhOzHp4XkCUhpRSlGgVTegDaBZHQJUPmfL9uP51fZQoaAZoCWgPQwjP86eN6gVjQJSGlFKUaBVN6ANoFkdAlRA8b3oLX3V9lChoBmgJaA9DCLVSCOQS1V5AlIaUUpRoFU3oA2gWR0CVFWP3i704dX2UKGgGaAloD0MIVb38ThM/ZECUhpRSlGgVTegDaBZHQJUa8Rh+fAd1fZQoaAZoCWgPQwiPqFDdXPplQJSGlFKUaBVN6ANoFkdAlSI7a7EpAnV9lChoBmgJaA9DCFLWbyamtz9AlIaUUpRoFUvwaBZHQJUimAMDwH91fZQoaAZoCWgPQwgArI4c6RVmQJSGlFKUaBVN6ANoFkdAlSTJbMX7+HV9lChoBmgJaA9DCHVZTGw+3GNAlIaUUpRoFU3oA2gWR0CVLlb9If8udX2UKGgGaAloD0MIfhmMEYkZYECUhpRSlGgVTegDaBZHQJUyLx4IKMN1fZQoaAZoCWgPQwhAoDNpU/09QJSGlFKUaBVNAAFoFkdAlTS1c6eXiXV9lChoBmgJaA9DCKZG6Gfq3l5AlIaUUpRoFU3oA2gWR0CVN+labF0gdX2UKGgGaAloD0MIwytJnmtVZUCUhpRSlGgVTegDaBZHQJU9DmV7hNx1fZQoaAZoCWgPQwhEozuInTJjQJSGlFKUaBVN6ANoFkdAlUNqRQrMDHV9lChoBmgJaA9DCHPzjegez2NAlIaUUpRoFU3oA2gWR0CVYkSJCSiedX2UKGgGaAloD0MIkL3e/XE6bkCUhpRSlGgVTZADaBZHQJVksRf4REp1fZQoaAZoCWgPQwjymld1VoJiQJSGlFKUaBVN6ANoFkdAlWUFI3BHkXV9lChoBmgJaA9DCAu3fCSl0WZAlIaUUpRoFU3oA2gWR0CVZoSDh99ddX2UKGgGaAloD0MIwf2AB4Z9YUCUhpRSlGgVTegDaBZHQJVqIFPi1iR1fZQoaAZoCWgPQwg2kgThCr5hQJSGlFKUaBVN6ANoFkdAlW9apo9LYnV9lChoBmgJaA9DCEBQbtt3C2RAlIaUUpRoFU3oA2gWR0CVcoLL6k6+dX2UKGgGaAloD0MIj/tW68STZUCUhpRSlGgVTegDaBZHQJV2TEjxCpp1fZQoaAZoCWgPQwjfwrrxbohiQJSGlFKUaBVN6ANoFkdAlX2PCAMDwHV9lChoBmgJaA9DCH0iT5KuuWVAlIaUUpRoFU3oA2gWR0CVgCFy7wrldX2UKGgGaAloD0MIXByVm6gRTUCUhpRSlGgVTS8BaBZHQJWINZTyaux1fZQoaAZoCWgPQwjHSWHeY8BiQJSGlFKUaBVN6ANoFkdAlYvgCKaXr3V9lChoBmgJaA9DCJiKjXkddmJAlIaUUpRoFU3oA2gWR0CVkDRhMJyAdX2UKGgGaAloD0MISBebVgqLYkCUhpRSlGgVTegDaBZHQJWShDUmUnp1fZQoaAZoCWgPQwgv+Z/83fM+QJSGlFKUaBVNAAFoFkdAlZLOLvTgEXV9lChoBmgJaA9DCH/7OnBOFWZAlIaUUpRoFU3oA2gWR0CVlQYr8R+SdX2UKGgGaAloD0MIW5pbISwYZUCUhpRSlGgVTegDaBZHQJWZXBqKxcF1fZQoaAZoCWgPQwikMzDyst1UQJSGlFKUaBVL5WgWR0CVnZyIpH7QdX2UKGgGaAloD0MINwAbEKETZUCUhpRSlGgVTegDaBZHQJWedlSS/0x1fZQoaAZoCWgPQwjNVl7yP0RjQJSGlFKUaBVN6ANoFkdAlbbHsXzlLnV9lChoBmgJaA9DCJT2Bl+Y1CBAlIaUUpRoFU0CAWgWR0CVt2L6k691dX2UKGgGaAloD0MIz2qBPSZtZkCUhpRSlGgVTegDaBZHQJW4zSro4dZ1fZQoaAZoCWgPQwgW3uUiPrFmQJSGlFKUaBVN6ANoFkdAlbkVBppN9HV9lChoBmgJaA9DCMPxfAbUYWBAlIaUUpRoFU3oA2gWR0CVus2EkB0ZdX2UKGgGaAloD0MI542TwjzoYUCUhpRSlGgVTegDaBZHQJW/MbuMMql1fZQoaAZoCWgPQwi95H/yd+5jQJSGlFKUaBVN6ANoFkdAlcYQ1m8M/nV9lChoBmgJaA9DCJhuEoNAt2VAlIaUUpRoFU3oA2gWR0CVz6eOXE61dX2UKGgGaAloD0MIqknwhjSuX0CUhpRSlGgVTegDaBZHQJXZYoG6f8N1fZQoaAZoCWgPQwjdQ8L3/jFjQJSGlFKUaBVN6ANoFkdAld++H31zyXV9lChoBmgJaA9DCH9PrFNlEWBAlIaUUpRoFU3oA2gWR0CV4nEg4ffXdX2UKGgGaAloD0MIknU4ukpxZkCUhpRSlGgVTegDaBZHQJXn2qOtGNJ1fZQoaAZoCWgPQwiCxHb3gBJjQJSGlFKUaBVN6ANoFkdAlegxYmsvI3V9lChoBmgJaA9DCAdfmEwVu11AlIaUUpRoFU3oA2gWR0CV7tIacZtOdX2UKGgGaAloD0MIaY6s/LKDZUCUhpRSlGgVTegDaBZHQJXznVAiV0N1fZQoaAZoCWgPQwi4PUFiu+9jQJSGlFKUaBVN6ANoFkdAlfR8qJ/G2nVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
|
replay.mp4
ADDED
Binary file (197 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 249.07395920940402, "std_reward": 23.84352976416805, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-19T18:02:41.792799"}
|