Upload PPO LunarLander-v2 trained agent
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: 273.24 +/- 19.37
|
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 0x79ba84a83ce0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79ba84a83d80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79ba84a83e20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79ba84a83ec0>", "_build": "<function ActorCriticPolicy._build at 0x79ba84a83f60>", "forward": "<function ActorCriticPolicy.forward at 0x79ba84a8c040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79ba84a8c0e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79ba84a8c180>", "_predict": "<function ActorCriticPolicy._predict at 0x79ba84a8c220>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79ba84a8c2c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79ba84a8c360>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79ba84a8c400>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79ba84bd4480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741302414738184997, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAE2svL2uKY2685jxuSmTyLRGLcC6IlAMOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "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:c32133589edf9d6ab445bd1dcf1e9b5099d9614bddefe2e9376cfb10b4e8db78
|
3 |
+
size 147438
|
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 0x79ba84a83ce0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79ba84a83d80>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79ba84a83e20>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79ba84a83ec0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x79ba84a83f60>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x79ba84a8c040>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x79ba84a8c0e0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79ba84a8c180>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x79ba84a8c220>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79ba84a8c2c0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79ba84a8c360>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x79ba84a8c400>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x79ba84bd4480>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1000448,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1741302414738184997,
|
30 |
+
"learning_rate": 0.0003,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"_last_obs": {
|
33 |
+
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAE2svL2uKY2685jxuSmTyLRGLcC6IlAMOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
35 |
+
},
|
36 |
+
"_last_episode_starts": {
|
37 |
+
":type:": "<class 'numpy.ndarray'>",
|
38 |
+
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -0.00044800000000000395,
|
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": 3908,
|
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 1,
|
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:cfefb2ee1dad3f5406824983d04c73e2bcd4f4370f0dcd7c092d75a17cb440d7
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:28aa8073f541975f51d7eee11a21c45f5798ed06f973510e084d5e0c611968aa
|
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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
|
2 |
+
- Python: 3.11.11
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.5.1+cu124
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.26.4
|
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 sha256:8060f2ce7264a4b6bab167db04a2120b2ba45d5ba6598c085027462314e38f4a
|
3 |
+
size 168510
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 273.24103069999995, "std_reward": 19.369751006818007, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-07T00:47:18.704946"}
|