🤖 Add 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 +8 -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: MlpPolicy
|
| 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: 256.01 +/- 22.63
|
| 20 |
+
name: mean_reward
|
| 21 |
+
verified: false
|
| 22 |
+
---
|
| 23 |
+
|
| 24 |
+
# **MlpPolicy** Agent playing **LunarLander-v2**
|
| 25 |
+
This is a trained model of a **MlpPolicy** 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 0x7fc9f8931ab0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc9f8931b40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc9f8931bd0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc9f8931c60>", "_build": "<function ActorCriticPolicy._build at 0x7fc9f8931cf0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc9f8931d80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc9f8931e10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc9f8931ea0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc9f8931f30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc9f8931fc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc9f8932050>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc9f89320e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc9f893c380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700940766024015749, "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:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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-6.2.0-36-generic-x86_64-with-glibc2.35 # 37~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Oct 9 15:34:04 UTC 2", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.2", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1"}}
|
ppo-LunarLander-v2.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:330a794b6d25d22fe54437d5fc6d6e2c02a493e80903861c5051af384c1cfaff
|
| 3 |
+
size 148209
|
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 0x7fc9f8931ab0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc9f8931b40>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc9f8931bd0>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc9f8931c60>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fc9f8931cf0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fc9f8931d80>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc9f8931e10>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc9f8931ea0>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fc9f8931f30>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc9f8931fc0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc9f8932050>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc9f89320e0>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7fc9f893c380>"
|
| 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": 1700940766024015749,
|
| 30 |
+
"learning_rate": 0.0003,
|
| 31 |
+
"tensorboard_log": null,
|
| 32 |
+
"_last_obs": {
|
| 33 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 34 |
+
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAHPSsD0UQK+6VnUBOoXoaLbWzSi6AApYtQAAgD8AAIA/wNOyvcOpQ7r7eD+6dbWJtqv3wzoOA205AACAPwAAAAAA9Zy90tD8PNaXhz1ffhe+96FOPID0Lj0AAAAAAAAAAGZqYT2mSoU/9ECbPVTB5755ffk8GGrTvQAAAAAAAAAAmmFsvHsgkrrmlDI8IbNptVolE7vbOl20AACAPwAAgD9mprq7SPuOusHVpLqaEZW1J6Teuae4vjkAAIA/AACAPyZNwz1Ir4y6NXTfOlW9YTUtdzY5qqsBugAAAAAAAIA/8/WePY8yfbotiZI4cw0vND8IdjuqVqe3AACAPwAAgD9mDwS9w6l2uspM7rf8K92yNNCWuueICzcAAIA/AACAP3NtIL4hG1A+AyxmParNeL4uwYO8ik4tPQAAAAAAAAAATT9gvY++crpRoj27ifNhNpXvObodRlo6AACAPwAAgD+antM84cyHuq9hjzvdrYw2GN2DOnzaproAAIA/AACAP82YOjxcXy66PkRdOeMnJzaJOnq7Nj4kNQAAgD8AAIA/INIePs6TSD8vVbS90wSXvj9NhDwyAe68AAAAAAAAAACmi7u9FKaUumtV4Ds2pfE1fWgCOwal5zQAAIA/AACAP5prHT1ca3a6pRNROv1t1jWmG1e7w+Z0uQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
|
| 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": 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:e3bf09ed9204d37566322a2328aa006b61a2ab1abe21a93b200c8047e703bc9e
|
| 3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:791834c48ba134d733526ace4dbc59204b758df3000a73cf916d331c8560bd14
|
| 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 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
- OS: Linux-6.2.0-36-generic-x86_64-with-glibc2.35 # 37~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Oct 9 15:34:04 UTC 2
|
| 2 |
+
- Python: 3.10.12
|
| 3 |
+
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.1.1+cu121
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 1.26.2
|
| 7 |
+
- Cloudpickle: 3.0.0
|
| 8 |
+
- Gymnasium: 0.28.1
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 256.0060335, "std_reward": 22.625704893488614, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-25T20:46:18.035079"}
|