Completed the UNIT01 of the DRL course.
Browse files- README.md +35 -1
- config.json +1 -0
- ppo_lunarlander_1M.zip +3 -0
- ppo_lunarlander_1M/_stable_baselines3_version +1 -0
- ppo_lunarlander_1M/data +99 -0
- ppo_lunarlander_1M/policy.optimizer.pth +3 -0
- ppo_lunarlander_1M/policy.pth +3 -0
- ppo_lunarlander_1M/pytorch_variables.pth +3 -0
- ppo_lunarlander_1M/system_info.txt +9 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
CHANGED
@@ -1,3 +1,37 @@
|
|
1 |
---
|
2 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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: 249.97 +/- 21.42
|
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 0x7cca9da43130>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cca9da431c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cca9da43250>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cca9da432e0>", "_build": "<function ActorCriticPolicy._build at 0x7cca9da43370>", "forward": "<function ActorCriticPolicy.forward at 0x7cca9da43400>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cca9da43490>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cca9da43520>", "_predict": "<function ActorCriticPolicy._predict at 0x7cca9da435b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cca9da43640>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cca9da436d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cca9da43760>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ccaa65fd8c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1701597021618903622, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_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": 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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo_lunarlander_1M.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e45d8162df76a263f0a65c9bda08559458a6e2967070ffaddf82906d43747484
|
3 |
+
size 148242
|
ppo_lunarlander_1M/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo_lunarlander_1M/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 0x7cca9da43130>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cca9da431c0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cca9da43250>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cca9da432e0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7cca9da43370>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7cca9da43400>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7cca9da43490>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cca9da43520>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7cca9da435b0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cca9da43640>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cca9da436d0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7cca9da43760>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7ccaa65fd8c0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1701597021618903622,
|
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": -0.015808000000000044,
|
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": 248,
|
55 |
+
"n_steps": 1024,
|
56 |
+
"gamma": 0.999,
|
57 |
+
"gae_lambda": 0.98,
|
58 |
+
"ent_coef": 0.01,
|
59 |
+
"vf_coef": 0.5,
|
60 |
+
"max_grad_norm": 0.5,
|
61 |
+
"batch_size": 64,
|
62 |
+
"n_epochs": 4,
|
63 |
+
"clip_range": {
|
64 |
+
":type:": "<class 'function'>",
|
65 |
+
":serialized:": "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"
|
66 |
+
},
|
67 |
+
"clip_range_vf": null,
|
68 |
+
"normalize_advantage": true,
|
69 |
+
"target_kl": null,
|
70 |
+
"observation_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
72 |
+
":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"dtype": "float32",
|
74 |
+
"bounded_below": "[ True True True True True True True True]",
|
75 |
+
"bounded_above": "[ True True True True True True True True]",
|
76 |
+
"_shape": [
|
77 |
+
8
|
78 |
+
],
|
79 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
80 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
81 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
82 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
83 |
+
"_np_random": null
|
84 |
+
},
|
85 |
+
"action_space": {
|
86 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
87 |
+
":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
88 |
+
"n": "4",
|
89 |
+
"start": "0",
|
90 |
+
"_shape": [],
|
91 |
+
"dtype": "int64",
|
92 |
+
"_np_random": null
|
93 |
+
},
|
94 |
+
"n_envs": 16,
|
95 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
98 |
+
}
|
99 |
+
}
|
ppo_lunarlander_1M/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f7ec1c7cd6c499c3ef1b6203c58f26254e0250767fb1a4b51f13ee0d42b82737
|
3 |
+
size 88490
|
ppo_lunarlander_1M/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7feea34c717a9c7351d40961fccd251d07a0b45b7768075df616049050afe20b
|
3 |
+
size 43762
|
ppo_lunarlander_1M/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_1M/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.1.0+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (185 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 249.9728197, "std_reward": 21.417552161225053, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-03T11:11:20.777984"}
|