ppo LunarLander from hf RL corse
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 +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 +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: 247.16 +/- 48.15
|
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 0x7c2022197d00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2022197d90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2022197e20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2022197eb0>", "_build": "<function ActorCriticPolicy._build at 0x7c2022197f40>", "forward": "<function ActorCriticPolicy.forward at 0x7c20221a0040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c20221a00d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c20221a0160>", "_predict": "<function ActorCriticPolicy._predict at 0x7c20221a01f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c20221a0280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c20221a0310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c20221a03a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c202213e680>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1705741679560220595, "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:": "gAWVIQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG/IkRSP2f2MAWyUS++MAXSUR0CahINRm9QGdX2UKGgGR0BuagnKGL1maAdNBQFoCEdAmoXuPvKEFnV9lChoBkdAcKou7YkE92gHS/1oCEdAmojuYlY2bXV9lChoBkdAcuX3Fkxyn2gHS/ZoCEdAmorRwZOzp3V9lChoBkdAcox0+C9RJmgHTfYBaAhHQJqMofgaWHF1fZQoaAZHQHA/SVObiIdoB00WAWgIR0Ca5Otw71ZldX2UKGgGR0Br7iUaAFxGaAdNagFoCEdAmuUOiJwbVHV9lChoBkdAcavFpPAO8WgHTdkBaAhHQJrlkmmce8x1fZQoaAZHQG9GMeXAuZloB03fAWgIR0Ca5a8XvYvndX2UKGgGR0Bh8uMXJo0zaAdN6ANoCEdAmucNa2WpqHV9lChoBkdAcaNpw0fozWgHS/ZoCEdAmucs94eLenV9lChoBkdAcg9fhMrVfGgHTRQBaAhHQJrncGmk30h1fZQoaAZHQHEpJJXhfjVoB00BAWgIR0Ca532DQJHBdX2UKGgGR0Bix1aQmu1XaAdN6ANoCEdAmuhWm1pj+nV9lChoBkdAZEmJ3xFy72gHTegDaAhHQJrpYhcJMQF1fZQoaAZHQG51vvjOs1doB00bAWgIR0Ca68b+cYqHdX2UKGgGR0BuTMRDkU9IaAdNBwFoCEdAmuxoHPeHi3V9lChoBkdAcNyhhYvFnGgHTQQBaAhHQJrtcMTewcJ1fZQoaAZHQHC21clgMMJoB0vqaAhHQJruNCrtE5R1fZQoaAZHQHErdPHktEpoB0v9aAhHQJruWJvYODt1fZQoaAZHQHAv8W0qpcZoB00EAWgIR0Ca7oD28IzFdX2UKGgGR0BxUJ7F85S4aAdNFwFoCEdAmu/UwaisXHV9lChoBkdAcFiE1l5GBmgHTQQBaAhHQJrxdymygPF1fZQoaAZHQHBY9znzQNVoB00bAWgIR0Ca8gmBvrGBdX2UKGgGR0BvNwLofSx8aAdL92gIR0Ca8imEoOQRdX2UKGgGR0Bu3ZqM3qA0aAdNIAFoCEdAmvJ08NhE0HV9lChoBkdAbwlA3T/hl2gHTR4BaAhHQJryugzxgAp1fZQoaAZHQG5DPf0mMOxoB0v7aAhHQJrz5VzZHut1fZQoaAZHQGLUOIhyKeloB03oA2gIR0Ca8/JCBwuNdX2UKGgGR0A2ugkTpPhyaAdLzGgIR0Ca9J6xPfsNdX2UKGgGR0BYnFN+LFXJaAdN6ANoCEdAmvgpooNNJ3V9lChoBkdAcP7eeWfK6mgHS+BoCEdAmvhTsIE8rHV9lChoBkdAcORJE6T4cmgHS/RoCEdAmvhgnx8UmHV9lChoBkdAcAswS8J2MmgHTRkBaAhHQJr405GSZBt1fZQoaAZHQGyTe4LCvX9oB0v9aAhHQJr5zHaN+9d1fZQoaAZHQHF2vexfOUtoB0voaAhHQJr6YtCiRGN1fZQoaAZHQHEFUdeY2KloB0vxaAhHQJr8yvzOHFh1fZQoaAZHQG+/Gx2St/5oB00YAWgIR0Ca/bsQNCqqdX2UKGgGR0BwT054nndPaAdNHgFoCEdAmv5VBQemvXV9lChoBkdAb7TNQCSzPmgHTQIBaAhHQJr+0uSOinJ1fZQoaAZHQG1gBfa6BiFoB00EAWgIR0Ca/4Zv1lGxdX2UKGgGR0ByVKxgRbr1aAdNMgFoCEdAmv+PW1+iJ3V9lChoBkdARElkJ8fFJmgHS85oCEdAmwDMYZVGTnV9lChoBkdAcbmGorFwUGgHS/NoCEdAmwGyfQKKHnV9lChoBkdAcRtIgeRxLmgHTekBaAhHQJsCoeKbayt1fZQoaAZHQHAFIqslsxhoB00ZAWgIR0CbAyA0sOG1dX2UKGgGR0BxWe7OE/SqaAdL9mgIR0CbA63HaN+9dX2UKGgGR0Bwi6GL1mJ4aAdNFwFoCEdAmwRm/nGKh3V9lChoBkdAcEttWuHN5mgHS/poCEdAmwX45PuXu3V9lChoBkdAYGUTSsr/bWgHTegDaAhHQJsGkHu7YkF1fZQoaAZHQHDjEa/ATIxoB0vxaAhHQJsGqtozvZ11fZQoaAZHQHAOJ/9YOlRoB03aAWgIR0CbBtJiRW92dX2UKGgGR0Bw4D2zv7WNaAdL82gIR0CbB0WnjyWidX2UKGgGR0BtFB7CzkZKaAdL92gIR0CbCHTnaFmGdX2UKGgGR0BwzQ9q1w5vaAdNKgFoCEdAmwlyUX531XV9lChoBkdAPEolUp/gBWgHS9VoCEdAmwoyHIp6QnV9lChoBkdAcX1P/JeVs2gHTTQBaAhHQJsKaSZBsyl1fZQoaAZHQHEUYWP91lpoB0v8aAhHQJsKolKK5091fZQoaAZHQHFFq5Gz8gpoB00gAWgIR0CbDUqUNayKdX2UKGgGR0Bu1hoRIz3zaAdNBwFoCEdAmw2d96Tnq3V9lChoBkdAbqWUQCjk/GgHS/loCEdAmw8/I4lyBHV9lChoBkdAb0SZkTYdyWgHTRIBaAhHQJsPlpVS4vx1fZQoaAZHQG6ghNVR1oxoB00DAWgIR0CbD9HTqjagdX2UKGgGR0BvluBUaQ3haAdL9GgIR0CbD81Q66redX2UKGgGR0Bu7mjqOcUeaAdNDwFoCEdAmxJE9QoCuHV9lChoBkdAbv8yE+Pik2gHTQkBaAhHQJsTTr3TNMZ1fZQoaAZHQG0WrG7z06JoB0vyaAhHQJsT2cTakAR1fZQoaAZHQG4ppqASWZ9oB004AWgIR0CbFl26TW5IdX2UKGgGR0BvZKbc45tFaAdNSQFoCEdAmxdvk7wKB3V9lChoBkdAcMLaPS2H+WgHS/5oCEdAmxe6nzg/DHV9lChoBkdAciDvoNd7fGgHTRABaAhHQJsY5JGvwE11fZQoaAZHQHCXr7Kq4pdoB0vwaAhHQJsZTiqABkt1fZQoaAZHQGONzvqkdmxoB03oA2gIR0CbGbZNO/L1dX2UKGgGR0Bwpn3wkPc0aAdL9WgIR0CbGhsHB1s+dX2UKGgGR0BwNjiiqQzUaAdNEgFoCEdAmxs1hkRSP3V9lChoBkdAcSDhhH9WIWgHTQABaAhHQJsdGbKA8Sx1fZQoaAZHQHKVn+yZ8a5oB01OAWgIR0CbHWXUpd8idX2UKGgGR0BgskO3DvVmaAdN6ANoCEdAmx7JMg2ZRnV9lChoBkdAcJe1IRRMvmgHS/loCEdAmyIIy9EkSnV9lChoBkdAcOKZflZHNGgHTQYBaAhHQJsiTdepn6F1fZQoaAZHQG63XNTtLL9oB012AWgIR0CbI6371qWUdX2UKGgGR0BwnQTtb9qDaAdL9GgIR0CbJDgzguRLdX2UKGgGR0BtllsWO6uoaAdNFQFoCEdAmyRoePq9oXV9lChoBkdAcWa5T6zmfWgHTVQBaAhHQJskxYigTRJ1fZQoaAZHQG+6xUFSsKdoB00YAWgIR0CbJ+4Ajps5dX2UKGgGR0BycGuTzND/aAdL9GgIR0CbKJHB1s+FdX2UKGgGR0BnX37+DOC5aAdN6ANoCEdAmymtPUKArnV9lChoBkdAcUQlN1yNoGgHTaIBaAhHQJstMHeJpFl1fZQoaAZHQFvCNMXaakRoB03oA2gIR0CbLkdjXnQqdX2UKGgGR0BwtP336AOKaAdNXQJoCEdAmzAz4k/r0XV9lChoBkdAcIF8F6iTMmgHTQABaAhHQJswlwkxASp1fZQoaAZHQF927NSqEOBoB03oA2gIR0CbMi1eSjgydX2UKGgGR0BArZqVQhwEaAdNBAFoCEdAmzJGi+L3sXV9lChoBkdATu7v/io86mgHS8ZoCEdAmzLWxt52QnV9lChoBkdAbhph9b5dnmgHTQ8BaAhHQJszI1m8M/h1fZQoaAZHQG/CeTFERapoB00cAWgIR0CbM7Qo1DSgdX2UKGgGR0Bts9vqC6H1aAdL9GgIR0CbNL55qubJdX2UKGgGR0BuFjEFW4mUaAdNOQFoCEdAmzTePeYUnHV9lChoBkdAbntzq8lHBmgHTZoBaAhHQJs2D3225QR1fZQoaAZHQEhYfOD8LrpoB0vAaAhHQJs2Nsk6cRV1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "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 sha256:37d9e438c601687771ef8d6d457003b0afc145a5595e5fcf7ac616104c05858f
|
3 |
+
size 148023
|
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 0x7c2022197d00>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2022197d90>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2022197e20>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2022197eb0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7c2022197f40>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7c20221a0040>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7c20221a00d0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c20221a0160>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7c20221a01f0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c20221a0280>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c20221a0310>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7c20221a03a0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7c202213e680>"
|
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": 1705741679560220595,
|
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": 310,
|
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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
80 |
+
"n_steps": 2048,
|
81 |
+
"gamma": 0.99,
|
82 |
+
"gae_lambda": 0.95,
|
83 |
+
"ent_coef": 0.0,
|
84 |
+
"vf_coef": 0.5,
|
85 |
+
"max_grad_norm": 0.5,
|
86 |
+
"batch_size": 64,
|
87 |
+
"n_epochs": 10,
|
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 sha256:0a0801ab9dacc0b422748566e226254462f8ab512585e9a011dc6d1b90bf00e6
|
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:e0adaede55a2eb6dd632598b43c2c8c651b5da8c3549a75c3b41168f027c4228
|
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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.1.0+cu121
|
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 (173 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 247.1645017, "std_reward": 48.14992268397442, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-01-20T09:52:26.218754"}
|