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 +94 -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 +7 -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: 244.26 +/- 14.26
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f656dbd8d30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f656dbd8dc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f656dbd8e50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f656dbd8ee0>", "_build": "<function ActorCriticPolicy._build at 0x7f656dbd8f70>", "forward": "<function ActorCriticPolicy.forward at 0x7f656dbdb040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f656dbdb0d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f656dbdb160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f656dbdb1f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f656dbdb280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f656dbdb310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f656dbd64b0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1671298606946890129, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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": 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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:64a21521aa4996aa5b76c7e7961e6d7de3a02956507479037ea8541e42cb21b5
|
3 |
+
size 147210
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f656dbd8d30>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f656dbd8dc0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f656dbd8e50>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f656dbd8ee0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f656dbd8f70>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f656dbdb040>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f656dbdb0d0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f656dbdb160>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f656dbdb1f0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f656dbdb280>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f656dbdb310>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f656dbd64b0>"
|
20 |
+
},
|
21 |
+
"verbose": 1,
|
22 |
+
"policy_kwargs": {},
|
23 |
+
"observation_space": {
|
24 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
25 |
+
":serialized:": "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",
|
26 |
+
"dtype": "float32",
|
27 |
+
"_shape": [
|
28 |
+
8
|
29 |
+
],
|
30 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
31 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
32 |
+
"bounded_below": "[False False False False False False False False]",
|
33 |
+
"bounded_above": "[False False False False False False False False]",
|
34 |
+
"_np_random": null
|
35 |
+
},
|
36 |
+
"action_space": {
|
37 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
38 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
39 |
+
"n": 4,
|
40 |
+
"_shape": [],
|
41 |
+
"dtype": "int64",
|
42 |
+
"_np_random": null
|
43 |
+
},
|
44 |
+
"n_envs": 16,
|
45 |
+
"num_timesteps": 1015808,
|
46 |
+
"_total_timesteps": 1000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1671298606946890129,
|
51 |
+
"learning_rate": 0.0003,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
|
56 |
+
},
|
57 |
+
"_last_obs": {
|
58 |
+
":type:": "<class 'numpy.ndarray'>",
|
59 |
+
":serialized:": "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"
|
60 |
+
},
|
61 |
+
"_last_episode_starts": {
|
62 |
+
":type:": "<class 'numpy.ndarray'>",
|
63 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.015808000000000044,
|
70 |
+
"ep_info_buffer": {
|
71 |
+
":type:": "<class 'collections.deque'>",
|
72 |
+
":serialized:": "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"
|
73 |
+
},
|
74 |
+
"ep_success_buffer": {
|
75 |
+
":type:": "<class 'collections.deque'>",
|
76 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
+
},
|
78 |
+
"_n_updates": 248,
|
79 |
+
"n_steps": 1024,
|
80 |
+
"gamma": 0.999,
|
81 |
+
"gae_lambda": 0.98,
|
82 |
+
"ent_coef": 0.01,
|
83 |
+
"vf_coef": 0.5,
|
84 |
+
"max_grad_norm": 0.5,
|
85 |
+
"batch_size": 64,
|
86 |
+
"n_epochs": 4,
|
87 |
+
"clip_range": {
|
88 |
+
":type:": "<class 'function'>",
|
89 |
+
":serialized:": "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"
|
90 |
+
},
|
91 |
+
"clip_range_vf": null,
|
92 |
+
"normalize_advantage": true,
|
93 |
+
"target_kl": null
|
94 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:17389d876760951069a279c2c629953600a13610dcc4457976bb9346169270ee
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:de221b6fe33cf022451190cc2e881f386e1eb8a162a460ef12b4838328ad5932
|
3 |
+
size 43201
|
ppo-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
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
|
2 |
+
Python: 3.8.16
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cu116
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (199 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 244.2645430710762, "std_reward": 14.264820775943162, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-17T18:16:53.858452"}
|