Lunar Lander V2 PPO trained model
Browse files- LunarLanderv2PPO.zip +3 -0
- LunarLanderv2PPO/_stable_baselines3_version +1 -0
- LunarLanderv2PPO/data +95 -0
- LunarLanderv2PPO/policy.optimizer.pth +3 -0
- LunarLanderv2PPO/policy.pth +3 -0
- LunarLanderv2PPO/pytorch_variables.pth +3 -0
- LunarLanderv2PPO/system_info.txt +7 -0
- README.md +37 -0
- config.json +1 -0
- replay.mp4 +0 -0
- results.json +1 -0
LunarLanderv2PPO.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:53843f1d87851ab3b49e12b4b389e326fcac2d19742f978c276f5a39d8fd198b
|
3 |
+
size 147416
|
LunarLanderv2PPO/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
LunarLanderv2PPO/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 0x7fcd4b068040>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcd4b0680d0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcd4b068160>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcd4b0681f0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fcd4b068280>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fcd4b068310>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fcd4b0683a0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcd4b068430>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fcd4b0684c0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcd4b068550>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcd4b0685e0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcd4b068670>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7fcd4b062720>"
|
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": 1674987572187461583,
|
52 |
+
"learning_rate": 0.001,
|
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": 310,
|
80 |
+
"n_steps": 2048,
|
81 |
+
"gamma": 0.999,
|
82 |
+
"gae_lambda": 0.99,
|
83 |
+
"ent_coef": 0.01,
|
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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null
|
95 |
+
}
|
LunarLanderv2PPO/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:92f78b07f8d8f937cac096edff9fcaadb52bff8934ac1bbc0b85407f0f0e766a
|
3 |
+
size 87929
|
LunarLanderv2PPO/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f46c43fc14610551583593b6968b65b96ad82e51795b154dba536eb6f5c373b4
|
3 |
+
size 43393
|
LunarLanderv2PPO/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
LunarLanderv2PPO/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: 260.48 +/- 25.34
|
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 0x7fcd4b068040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcd4b0680d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcd4b068160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcd4b0681f0>", "_build": "<function ActorCriticPolicy._build at 0x7fcd4b068280>", "forward": "<function ActorCriticPolicy.forward at 0x7fcd4b068310>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fcd4b0683a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcd4b068430>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcd4b0684c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcd4b068550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcd4b0685e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcd4b068670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcd4b062720>"}, "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": 1674987572187461583, "learning_rate": 0.001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/UGJN0vGp/IWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.99, "ent_coef": 0.01, "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, "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 (222 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 260.4762743285587, "std_reward": 25.340575888569457, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-29T11:09:54.570770"}
|