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: 280.03 +/- 19.66
|
| 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 0x7ef2ecaf8a40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ef2ecaf8ae0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ef2ecaf8b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ef2ecaf8c20>", "_build": "<function ActorCriticPolicy._build at 0x7ef2ecaf8cc0>", "forward": "<function ActorCriticPolicy.forward at 0x7ef2ecaf8d60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ef2ecaf8e00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ef2ecaf8ea0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ef2ecaf8f40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ef2ecaf8fe0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ef2ecaf9080>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ef2ecaf9120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ef2eca60480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1003520, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1773447200808302967, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9gAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWgAAAAAAAAACAmLM99l2jPxpvMj/0iRa/vxLcPO70az4AAAAAAAAAAMYoFj7aBUY+VgCQvmsUk756Pya7Fnh+vAAAAAAAAAAAZr7xvXGOMjzlRCg+EEhPvuTX3rvKPQO9AAAAAAAAAABWRXa+cH6CPx4p5b57LsK+rL+QvsFqJL4AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVeAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksEhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 980, "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": 4, "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEyL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTIvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+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-6.6.113+-x86_64-with-glibc2.35 # 1 SMP Mon Feb 2 12:27:57 UTC 2026", "Python": "3.12.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.10.0+cu128", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.2", "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 sha256:2342c29e17e3057814c131eec9f6aa8ae11ec9e882ac899326a68c93078bf6a2
|
| 3 |
+
size 148612
|
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 0x7ef2ecaf8a40>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ef2ecaf8ae0>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ef2ecaf8b80>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ef2ecaf8c20>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7ef2ecaf8cc0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7ef2ecaf8d60>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7ef2ecaf8e00>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ef2ecaf8ea0>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7ef2ecaf8f40>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ef2ecaf8fe0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ef2ecaf9080>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7ef2ecaf9120>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7ef2eca60480>"
|
| 21 |
+
},
|
| 22 |
+
"verbose": 1,
|
| 23 |
+
"policy_kwargs": {},
|
| 24 |
+
"num_timesteps": 1003520,
|
| 25 |
+
"_total_timesteps": 1000000,
|
| 26 |
+
"_num_timesteps_at_start": 0,
|
| 27 |
+
"seed": null,
|
| 28 |
+
"action_noise": null,
|
| 29 |
+
"start_time": 1773447200808302967,
|
| 30 |
+
"learning_rate": 0.0003,
|
| 31 |
+
"tensorboard_log": null,
|
| 32 |
+
"_last_obs": {
|
| 33 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 34 |
+
":serialized:": "gAWV9gAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWgAAAAAAAAACAmLM99l2jPxpvMj/0iRa/vxLcPO70az4AAAAAAAAAAMYoFj7aBUY+VgCQvmsUk756Pya7Fnh+vAAAAAAAAAAAZr7xvXGOMjzlRCg+EEhPvuTX3rvKPQO9AAAAAAAAAABWRXa+cH6CPx4p5b57LsK+rL+QvsFqJL4AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBEsIhpSMAUOUdJRSlC4="
|
| 35 |
+
},
|
| 36 |
+
"_last_episode_starts": {
|
| 37 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 38 |
+
":serialized:": "gAWVeAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksEhZSMAUOUdJRSlC4="
|
| 39 |
+
},
|
| 40 |
+
"_last_original_obs": null,
|
| 41 |
+
"_episode_num": 0,
|
| 42 |
+
"use_sde": false,
|
| 43 |
+
"sde_sample_freq": -1,
|
| 44 |
+
"_current_progress_remaining": -0.0035199999999999676,
|
| 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": 980,
|
| 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": 4,
|
| 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 sha256:97eaae1394e8dc22e4158d4c8c9ee390ad77011af1ecfd78fedb6cbd66f2635a
|
| 3 |
+
size 88695
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bdb861a47aacb6db235fe4d8ddaa3f4b0e47369814e5bd337d1766f2f3d89d0a
|
| 3 |
+
size 44095
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:07c7431cf6005e7d8f367d79e995f63e2f9b981a37e3437b795d058f9af4308b
|
| 3 |
+
size 1261
|
ppo-LunarLander-v2/system_info.txt
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
- OS: Linux-6.6.113+-x86_64-with-glibc2.35 # 1 SMP Mon Feb 2 12:27:57 UTC 2026
|
| 2 |
+
- Python: 3.12.12
|
| 3 |
+
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.10.0+cu128
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 2.0.2
|
| 7 |
+
- Cloudpickle: 3.1.2
|
| 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:e356ff95107c57f616671f8163e17b6fa823bbbc9350340300433892a6910464
|
| 3 |
+
size 151262
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 280.027047, "std_reward": 19.66419672021056, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2026-03-14T01:01:40.120546"}
|