Upload PPO LunarLander-v2 trained agent (2)
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 +95 -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: 244.85 +/- 17.73
|
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 0x7f7700ae2dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7700ae2e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7700ae2ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7700ae2f70>", "_build": "<function ActorCriticPolicy._build at 0x7f7700a66040>", "forward": "<function ActorCriticPolicy.forward at 0x7f7700a660d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7700a66160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7700a661f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7700a66280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7700a66310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7700a663a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7700a66430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7700ae13c0>"}, "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": 1676331374746763023, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+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-5.10.147+-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"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4774df61a8f15ffc8b4e98651a236c0b8be6e6f8e8224b413bd2d547dfc7865e
|
3 |
+
size 147420
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ppo-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 0x7f7700ae2dc0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7700ae2e50>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7700ae2ee0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7700ae2f70>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f7700a66040>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f7700a660d0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7700a66160>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7700a661f0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f7700a66280>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7700a66310>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7700a663a0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7700a66430>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7f7700ae13c0>"
|
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": 1676331374746763023,
|
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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null
|
95 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:485fe29ad45859fcce12df3428043cae2c6cdaf3d716c77b96101e4656f455d8
|
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:e1edd6b765ceffdcfd5e384968e229469c993a37e5440a76d8f7787fd3e1beb3
|
3 |
+
size 43393
|
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-5.10.147+-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
|
replay.mp4
ADDED
Binary file (220 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 244.85128103976575, "std_reward": 17.731077008453866, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-14T00:08:53.780113"}
|