Solving Deep RL Course
Browse files- .gitattributes +1 -0
- 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 +99 -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 +9 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
36 |
+
replay.mp4 filter=lfs diff=lfs merge=lfs -text
|
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: 249.71 +/- 18.77
|
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 0x7c019d9776a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c019d977740>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c019d9777e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c019d977880>", "_build": "<function ActorCriticPolicy._build at 0x7c019d977920>", "forward": "<function ActorCriticPolicy.forward at 0x7c019d9779c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c019d977a60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c019d977b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7c019d977ba0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c019d977c40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c019d977ce0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c019d977d80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c019dad7b80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1755233649849032288, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9e52181a9ebb576594ba086765cda8f2ca36ac3d424354e9e8627130068d7370
|
3 |
+
size 148112
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/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 0x7c019d9776a0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c019d977740>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c019d9777e0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c019d977880>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7c019d977920>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7c019d9779c0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7c019d977a60>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c019d977b00>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7c019d977ba0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c019d977c40>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c019d977ce0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7c019d977d80>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7c019dad7b80>"
|
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": 1755233649849032288,
|
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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
|
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 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "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",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
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 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
+
}
|
99 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:05fd43d29afa892232c78ffbf6a972d37b382c9fca790fdc307e180aed90203a
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7a6af2c3f7074c654b9eaaa37258440ae29b7426902e8578f6296d48f29928e0
|
3 |
+
size 43762
|
ppo-LunarLander-v2/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-v2/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
|
2 |
+
- Python: 3.11.13
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.6.0+cu124
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 2.0.2
|
7 |
+
- Cloudpickle: 3.1.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8bf9297367d17ef04844e9d73e086e470366dde722bad386be61a71f17815db6
|
3 |
+
size 166600
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 249.70974109999997, "std_reward": 18.769469438886173, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-08-15T05:26:02.235386"}
|