Upload PPO LunarLander-v2 trained agent
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: 262.27 +/- 19.54
|
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 0x7ffa5bed2f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffa5bed3010>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffa5bed30a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffa5bed3130>", "_build": "<function ActorCriticPolicy._build at 0x7ffa5bed31c0>", "forward": "<function ActorCriticPolicy.forward at 0x7ffa5bed3250>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ffa5bed32e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffa5bed3370>", "_predict": "<function ActorCriticPolicy._predict at 0x7ffa5bed3400>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffa5bed3490>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffa5bed3520>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffa5bed35b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ffa5be70080>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719584186854422511, "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, "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": 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:": "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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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Tue Jun 18 14:18:04 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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:ce849afe9da511a318bc308378a2c51032e8bc08310098bc511820801d710175
|
3 |
+
size 148084
|
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 0x7ffa5bed2f80>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffa5bed3010>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffa5bed30a0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffa5bed3130>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7ffa5bed31c0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7ffa5bed3250>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7ffa5bed32e0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffa5bed3370>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7ffa5bed3400>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffa5bed3490>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffa5bed3520>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffa5bed35b0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7ffa5be70080>"
|
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": 1719584186854422511,
|
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:": "gAWVQwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG8TtIkJKJ6MAWyUTT8BjAF0lEdAlyNtNBWxQnV9lChoBkdAbKQ2ETQE6mgHTWABaAhHQJcjdw1ivxJ1fZQoaAZHQHJEoz7/GVBoB01PAWgIR0CXNp2lEZzgdX2UKGgGR0BxTq9alk6LaAdNUQFoCEdAlzaq7I1cdHV9lChoBkdAcb2gHNX5nGgHTVYBaAhHQJc3BG2Culp1fZQoaAZHQHCMR0yP+4toB01NAWgIR0CXN7MdtEXtdX2UKGgGR0Bsi8qe9SMtaAdNWQFoCEdAlzfB+WnjyXV9lChoBkdAcIk0kGA09GgHTZoBaAhHQJc4IQxvegt1fZQoaAZHQGtsIWP91lpoB003AWgIR0CXOmJZ4fOldX2UKGgGR0BxOMXO4XoDaAdNJgFoCEdAlz2xGDtgKHV9lChoBkdAb5m+aBqbjWgHTTMBaAhHQJc+CipNsWR1fZQoaAZHQG6BzNUwSJ1oB00/AWgIR0CXQP0VJtiydX2UKGgGR0BsZjHsC1Z1aAdNLgFoCEdAl0E7qhUR4HV9lChoBkdAciJq/dqL0mgHTUUBaAhHQJdCH24/eLx1fZQoaAZHQGywUHQhOgxoB00WAWgIR0CXQoUsnRb9dX2UKGgGR0BxK3xwyZa3aAdNmQFoCEdAl0MZXEIgNnV9lChoBkdAb/puPV/c32gHTSYBaAhHQJdDbRjSXt11fZQoaAZHQHDFGMS9M9NoB01fAWgIR0CXQ6DPGACodX2UKGgGR0Bxy4e7tiQUaAdNagFoCEdAl0QmOAAhjnV9lChoBkdAcGyrPt2LYWgHTUMBaAhHQJdE8/eLvTh1fZQoaAZHQHGK4msvIwNoB01JAWgIR0CXRSjGkvbodX2UKGgGR0BxQXGCI1tPaAdNRAFoCEdAl0VQlF+d9XV9lChoBkdAcKehllK9PGgHTaYBaAhHQJdF6T5ftyB1fZQoaAZHQG+NTn7pFCtoB02IAWgIR0CXRh9ETg2qdX2UKGgGR0BwmicwxnFpaAdNKAFoCEdAl0ZVsYVIqnV9lChoBkdAcaVsPJ7swGgHTUEBaAhHQJdJbw3HaOB1fZQoaAZHQHCzHuqm0mdoB01aAWgIR0CXShmlZX+3dX2UKGgGR0BxHkI3R5TqaAdNSgFoCEdAl0wJgLJCB3V9lChoBkdAcIODSPU8WGgHTTYBaAhHQJdMkT238XN1fZQoaAZHQHKMqUJOWSloB01QAWgIR0CXTTU8V58jdX2UKGgGR0Bw1DlfZ26kaAdNNQFoCEdAl029AC4jKXV9lChoBkdAQS2LBKtga2gHS/poCEdAl06tKujh1nV9lChoBkdAbma+Jxeb/mgHTScBaAhHQJdOwyylenh1fZQoaAZHQHKOkU9IPLBoB01gAWgIR0CXTySDAaegdX2UKGgGR0Bt6TBGhEjPaAdNagFoCEdAl08ueJ53T3V9lChoBkdAci95Qgs9S2gHTVMBaAhHQJdPaSbH6uZ1fZQoaAZHQG9B+umrKeVoB007AWgIR0CXT8yxA0KrdX2UKGgGR0BwL8wxnFo+aAdNQAFoCEdAl1CU3GXHBHV9lChoBkdAcb+5f+jubGgHTV4BaAhHQJdQpwm3OOd1fZQoaAZHQHCqEMoc7yRoB03rAWgIR0CXUV+x4Y78dX2UKGgGR0Bwn6M0gr6MaAdNVgFoCEdAl1GrhR64UnV9lChoBkc/5nV3EAHVw2gHTQYBaAhHQJdSPGBFuvV1fZQoaAZHQHBkNmthd+poB00mAWgIR0CXU497WuoxdX2UKGgGR0BuClzGPxQSaAdNGwFoCEdAl1Vst5D7ZXV9lChoBkdAcPt7IDHOr2gHTUABaAhHQJdWUBsANod1fZQoaAZHQHIxeWv8qF1oB00jAWgIR0CXVtKHO8kEdX2UKGgGR0BtjpBsyi22aAdNMgFoCEdAl1bmNedCmnV9lChoBkdAcdY1oxpL3GgHTRIBaAhHQJdXjhJiAlR1fZQoaAZHQG19awMYuTRoB00rAWgIR0CXV/B3zMA4dX2UKGgGR0AjOhRqGlANaAdNCgFoCEdAl1gBSP2f03V9lChoBkdAa9SyxA0KqmgHTTYBaAhHQJdYvhddE9d1fZQoaAZHQG08jKYAsCloB01OAWgIR0CXWTlaKUFCdX2UKGgGR0BwcVSiudPMaAdNSQFoCEdAl1mx7NSqEXV9lChoBkdAb7KSq2jO9mgHTSoBaAhHQJdaBnqVyFR1fZQoaAZHQHCUV01ZTydoB001AWgIR0CXbNDNyHVPdX2UKGgGR0BwdamZVn27aAdNUQFoCEdAl285hfBvaXV9lChoBkdAck8eHSF492gHTVABaAhHQJdvpTS9du51fZQoaAZHQHDad29tdiVoB01bAWgIR0CXcU0wrUb2dX2UKGgGR0Bv1dfTkQwsaAdNTAFoCEdAl3J7IYFaCHV9lChoBkdAcTtoDgZTAGgHTS8BaAhHQJd0YMrmQsB1fZQoaAZHQHB6c4YJmd1oB004AWgIR0CXdVmXPZ7HdX2UKGgGR0BtxIKBun/DaAdNUgFoCEdAl3Zp6po9LnV9lChoBkdAbJLFEy+HrWgHTUABaAhHQJd2ih+OOsF1fZQoaAZHQGw47Kq4pc5oB00zAWgIR0CXd2Xsw+MZdX2UKGgGR0Bu7fTI/7iyaAdNTQFoCEdAl3eKbz9S/HV9lChoBkdAa7OjdpItlWgHTS4BaAhHQJd4prEcbR51fZQoaAZHQHKCWkzoEB9oB00+AWgIR0CXeZDUVi4KdX2UKGgGR0BxwxXmvGIbaAdNVAFoCEdAl3mkY0l7dHV9lChoBkdAbzt4XXRPXWgHTWYBaAhHQJd5w7dSEUV1fZQoaAZHQHIbc4gieNFoB03ZAWgIR0CXehLn9vS/dX2UKGgGR0Bs/IJgLJCCaAdNLgFoCEdAl3sfTPSlWXV9lChoBkdAcULXcQAdXGgHTVABaAhHQJd73jbSJCV1fZQoaAZHQHCEUpRXOnloB00sAWgIR0CXfCv+OwPidX2UKGgGR0Buncw35vcaaAdNIgFoCEdAl3ztPLxI8XV9lChoBkdAcqyYrJ8v3GgHTRkBaAhHQJd/J+Zw4sF1fZQoaAZHQG+PMKCxu89oB01FAWgIR0CXf+ci4axYdX2UKGgGR0BwNnKbKA8TaAdNOgFoCEdAl4FkzbeuWHV9lChoBkdAbrAeI2wV02gHTS0BaAhHQJeB580DU3J1fZQoaAZHQG+wT5ftx+9oB01EAWgIR0CXgfM+u/1ydX2UKGgGR0BwTaCUX531aAdNFAFoCEdAl4JD+zdDY3V9lChoBkdAbmsQFs54nmgHTSEBaAhHQJeD3+R5kbx1fZQoaAZHQGtTHQhOgxtoB004AWgIR0CXhJN8VpK0dX2UKGgGR0ByK0rOJLuhaAdNHQFoCEdAl4VptJnQIHV9lChoBkdAcQCnyup0fmgHTWUBaAhHQJeG5fgJkXl1fZQoaAZHQG13mMGX5WRoB011AWgIR0CXhw6IFeOXdX2UKGgGR0BwHm15Sm65aAdNSgFoCEdAl4hvZIxxk3V9lChoBkdAcEje7L+xW2gHTXMBaAhHQJeJs97ngYR1fZQoaAZHQG0UwWnCO3loB00zAWgIR0CXjAtQbdaddX2UKGgGR0Br/oRwqAjIaAdNTQFoCEdAl4xP1lGwzXV9lChoBkdAcXruCPIXCWgHTZQBaAhHQJeMhNIsiB51fZQoaAZHQG1rP/aQFLZoB01KAWgIR0CXjn+mm+CcdX2UKGgGR0ByBu+ajN6gaAdNRgFoCEdAl481rRBu43V9lChoBkdAcJR3o9s7+2gHTV0BaAhHQJePx55Z8rt1fZQoaAZHQHDCf0I1LrZoB01eAWgIR0CXj9ykKu0UdX2UKGgGR0BVMdp7CzkZaAdN6ANoCEdAl5B6yOaOP3V9lChoBkdAbFFFc6eXiWgHTTEBaAhHQJeQuSEDhcZ1fZQoaAZHQHCg+SB9TgloB01IAWgIR0CXkOS26TW5dX2UKGgGR0Byh8qe9SMtaAdNFgFoCEdAl5HKkhzNlnV9lChoBkdAco+zoUzsQmgHTUMBaAhHQJeR7aHsTnJ1fZQoaAZHQHFZxZyMkyFoB00cAWgIR0CXkwwPy08edWUu"
|
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
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 sha256:0f34978ea9e78217e78cad2172c7112c895ed05f0c23b2e76f35ca5bb7134dce
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:71248e4b4039294f39d6024cc14a644c7fa5c44d4689488848a1db5decf2ace5
|
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 Tue Jun 18 14:18:04 UTC 2024
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.3.0+cu121
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.25.2
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (180 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 262.26504476931495, "std_reward": 19.543231098553598, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-28T14:50:47.481942"}
|