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 +95 -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 +7 -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: 244.69 +/- 20.40
|
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 0x7f4255ba7dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4255ba7e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4255ba7ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4255ba7f70>", "_build": "<function ActorCriticPolicy._build at 0x7f4255ba9040>", "forward": "<function ActorCriticPolicy.forward at 0x7f4255ba90d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4255ba9160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4255ba91f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4255ba9280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4255ba9310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4255ba93a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4255ba9430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f4255baa300>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679639114451526788, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:442512c49f1de4fd69893d6829c225e92a14fa9f7c8e630a6b4cd327e3d4db44
|
3 |
+
size 147417
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,95 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f4255ba7dc0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4255ba7e50>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4255ba7ee0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4255ba7f70>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f4255ba9040>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f4255ba90d0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4255ba9160>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4255ba91f0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f4255ba9280>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4255ba9310>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4255ba93a0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4255ba9430>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f4255baa300>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"dtype": "float32",
|
28 |
+
"_shape": [
|
29 |
+
8
|
30 |
+
],
|
31 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
32 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
33 |
+
"bounded_below": "[False False False False False False False False]",
|
34 |
+
"bounded_above": "[False False False False False False False False]",
|
35 |
+
"_np_random": null
|
36 |
+
},
|
37 |
+
"action_space": {
|
38 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
39 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
40 |
+
"n": 4,
|
41 |
+
"_shape": [],
|
42 |
+
"dtype": "int64",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 16,
|
46 |
+
"num_timesteps": 1015808,
|
47 |
+
"_total_timesteps": 1000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1679639114451526788,
|
52 |
+
"learning_rate": 0.0003,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'numpy.ndarray'>",
|
60 |
+
":serialized:": "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"
|
61 |
+
},
|
62 |
+
"_last_episode_starts": {
|
63 |
+
":type:": "<class 'numpy.ndarray'>",
|
64 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
65 |
+
},
|
66 |
+
"_last_original_obs": null,
|
67 |
+
"_episode_num": 0,
|
68 |
+
"use_sde": false,
|
69 |
+
"sde_sample_freq": -1,
|
70 |
+
"_current_progress_remaining": -0.015808000000000044,
|
71 |
+
"ep_info_buffer": {
|
72 |
+
":type:": "<class 'collections.deque'>",
|
73 |
+
":serialized:": "gAWVdhAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIGjbK+s1ScUCUhpRSlIwBbJRNdQGMAXSUR0CbMwuNxVABdX2UKGgGaAloD0MIFOeoo6OEckCUhpRSlGgVTUQBaBZHQJsz9z1bqyJ1fZQoaAZoCWgPQwgcJET5Al5vQJSGlFKUaBVNVAFoFkdAmzQtqxkd3nV9lChoBmgJaA9DCHOfHAVI73FAlIaUUpRoFU0TAWgWR0CbNftHxz7udX2UKGgGaAloD0MIw5/hzRq7bECUhpRSlGgVTVIBaBZHQJs4KqT8pCt1fZQoaAZoCWgPQwjaU3JOrBJxQJSGlFKUaBVNUwFoFkdAmzhdqcmShnV9lChoBmgJaA9DCEsEqn8Q6XJAlIaUUpRoFU1iAWgWR0CbOGtDUmUodX2UKGgGaAloD0MIhzWVRWFsbUCUhpRSlGgVTWMBaBZHQJs4bCcf/3p1fZQoaAZoCWgPQwjFU480eF9xQJSGlFKUaBVNNwFoFkdAmziIvSMLnnV9lChoBmgJaA9DCL5nJEIj2kJAlIaUUpRoFU0TAWgWR0CbOTuPmxMWdX2UKGgGaAloD0MI74y2KsmvcECUhpRSlGgVTVUBaBZHQJs5efWcz691fZQoaAZoCWgPQwh7pMFt7WVxQJSGlFKUaBVNZQFoFkdAmzna2a2F4HV9lChoBmgJaA9DCOT09XxNzm5AlIaUUpRoFU1aAWgWR0CbOidhRZU2dX2UKGgGaAloD0MI2bRSCGQwc0CUhpRSlGgVTUYBaBZHQJs65v99+gF1fZQoaAZoCWgPQwjpgY/BSoNwQJSGlFKUaBVNAgJoFkdAmzwMJIDoyXV9lChoBmgJaA9DCA37PbFOZXBAlIaUUpRoFU1bAWgWR0CbPAzEaVD8dX2UKGgGaAloD0MIQSjv42inbkCUhpRSlGgVTSsBaBZHQJs9Huv2XcB1fZQoaAZoCWgPQwjRzJNriolwQJSGlFKUaBVNUwFoFkdAmz1Z1zQu3HV9lChoBmgJaA9DCLlQ+dey7HBAlIaUUpRoFU0sAWgWR0CbPVeLehwmdX2UKGgGaAloD0MINnUeFf//NECUhpRSlGgVS/9oFkdAmz+TK9wm3XV9lChoBmgJaA9DCD3S4LZ2MXBAlIaUUpRoFU0cAWgWR0CbQfyI55qudX2UKGgGaAloD0MIsAJ8t7kOcECUhpRSlGgVTScBaBZHQJtCHVOKwZB1fZQoaAZoCWgPQwgPYJFfv7RwQJSGlFKUaBVNgQFoFkdAm0IobGWD6HV9lChoBmgJaA9DCNBGrpvSJW9AlIaUUpRoFU1KAWgWR0CbQjfBN21VdX2UKGgGaAloD0MIMjhKXp3vcECUhpRSlGgVTUgBaBZHQJtCd47ihnJ1fZQoaAZoCWgPQwhTr1sExjpwQJSGlFKUaBVNTQFoFkdAm0J4MOPNmnV9lChoBmgJaA9DCPYpx2Sx3XFAlIaUUpRoFU0rAWgWR0CbQy3dKujidX2UKGgGaAloD0MIBcJOsaqGckCUhpRSlGgVTWsBaBZHQJtDVgv114h1fZQoaAZoCWgPQwiGWWjnNDFuQJSGlFKUaBVNRgFoFkdAm0OTZg5R0nV9lChoBmgJaA9DCOBpMuMtHnBAlIaUUpRoFU04AWgWR0CbREZqmCRPdX2UKGgGaAloD0MIpdx9jo+SSUCUhpRSlGgVS/ZoFkdAm0Tnqmj0tnV9lChoBmgJaA9DCBqojH9ftHBAlIaUUpRoFU0uAWgWR0CbRRGDL8rJdX2UKGgGaAloD0MIbEHvjSGtbUCUhpRSlGgVTUIBaBZHQJtFik1uR9x1fZQoaAZoCWgPQwjtYprp3kxvQJSGlFKUaBVNPwFoFkdAm0apn+Q2dnV9lChoBmgJaA9DCCJt40/UCXJAlIaUUpRoFU1zAWgWR0CbR9sl9jPOdX2UKGgGaAloD0MId7rzxLNjcECUhpRSlGgVTV4BaBZHQJtJ+QwK0D51fZQoaAZoCWgPQwjK/nkasBBxQJSGlFKUaBVNQQFoFkdAm0t8/D+BH3V9lChoBmgJaA9DCJxu2SH+Sm9AlIaUUpRoFU06AWgWR0CbS5yC4BmxdX2UKGgGaAloD0MIwvnUsUp8ckCUhpRSlGgVTU8BaBZHQJtMLZqVQhx1fZQoaAZoCWgPQwhkO99PTQZwQJSGlFKUaBVNUwFoFkdAm0w7ZSNwSHV9lChoBmgJaA9DCJoiwOlduHBAlIaUUpRoFU1GAWgWR0CbTEn1FpfydX2UKGgGaAloD0MI3iBaK9qebkCUhpRSlGgVTTMBaBZHQJtM13kgfU51fZQoaAZoCWgPQwjf3coSHXpyQJSGlFKUaBVNDgFoFkdAm0zhL5AQhHV9lChoBmgJaA9DCGqEfqYelHFAlIaUUpRoFU00AWgWR0CbTUg9eQdTdX2UKGgGaAloD0MIVmKelXSscECUhpRSlGgVTXgBaBZHQJtOAYIjW091fZQoaAZoCWgPQwjD8ufbgsxvQJSGlFKUaBVNdgFoFkdAm2ave54GEHV9lChoBmgJaA9DCGSRJt4BhmtAlIaUUpRoFU00AWgWR0CbZsGZeAuqdX2UKGgGaAloD0MInxwFiILqcECUhpRSlGgVTTkBaBZHQJtniC2+fyx1fZQoaAZoCWgPQwicUfNVcl5tQJSGlFKUaBVNWAFoFkdAm2fI1+AmRnV9lChoBmgJaA9DCO/mqQ65cFFAlIaUUpRoFUvmaBZHQJtpRyQxN7B1fZQoaAZoCWgPQwgHfentz5xuQJSGlFKUaBVNVwFoFkdAm2l2ZRbbDnV9lChoBmgJaA9DCE8eFmpNMHNAlIaUUpRoFU1GAWgWR0Cbai2Cdz4ldX2UKGgGaAloD0MINzXQfE7uckCUhpRSlGgVTRUBaBZHQJtsX7el9Bt1fZQoaAZoCWgPQwhM4NbdvN9sQJSGlFKUaBVNIwFoFkdAm2x0uctoSXV9lChoBmgJaA9DCJ1GWipvl25AlIaUUpRoFU1DAWgWR0CbbhU7CBPLdX2UKGgGaAloD0MIaJdvfVg6bUCUhpRSlGgVTTcBaBZHQJtuKYb83uN1fZQoaAZoCWgPQwisU+V7BltwQJSGlFKUaBVNVAFoFkdAm248PSUkfXV9lChoBmgJaA9DCLK5ap4jcg9AlIaUUpRoFUv6aBZHQJtuRR77bcp1fZQoaAZoCWgPQwhCzvv/OOBvQJSGlFKUaBVNRgFoFkdAm273DrJKa3V9lChoBmgJaA9DCH9ne/TGiXBAlIaUUpRoFU1uAWgWR0Cbb3pV0cOtdX2UKGgGaAloD0MImmA417CrcECUhpRSlGgVTUYBaBZHQJtvlzPrv9d1fZQoaAZoCWgPQwjzPSMR2gFxQJSGlFKUaBVNZgFoFkdAm2+r3Gn4wnV9lChoBmgJaA9DCEG7Q4oBBHNAlIaUUpRoFU0GAWgWR0Cbb+tW+49YdX2UKGgGaAloD0MIUBpqFJJwb0CUhpRSlGgVTVABaBZHQJtwrMHKOkt1fZQoaAZoCWgPQwgnvtpRnOVHQJSGlFKUaBVL72gWR0CbcbG0eEIxdX2UKGgGaAloD0MIDM11GmmjbUCUhpRSlGgVTR4BaBZHQJtyE/X5FgF1fZQoaAZoCWgPQwjRAx+DlfhvQJSGlFKUaBVNagFoFkdAm3JA1ejVQXV9lChoBmgJaA9DCF+y8WCLE0dAlIaUUpRoFUvraBZHQJtzX212JSB1fZQoaAZoCWgPQwgjTFEuDVpvQJSGlFKUaBVNVAFoFkdAm3OnOv+wT3V9lChoBmgJaA9DCElMUMO3VkJAlIaUUpRoFUv3aBZHQJtzptBOYY11fZQoaAZoCWgPQwivP4nPnXpAQJSGlFKUaBVL+mgWR0CbdSU/fO2RdX2UKGgGaAloD0MIY30Dk5tPbkCUhpRSlGgVTRsBaBZHQJt2L1lGwzN1fZQoaAZoCWgPQwgVxausbS5wQJSGlFKUaBVNMAFoFkdAm3bOuA7Pp3V9lChoBmgJaA9DCNRkxttKLXJAlIaUUpRoFU05AWgWR0CbdwVz6rNodX2UKGgGaAloD0MI+P2bFye+cECUhpRSlGgVTRcBaBZHQJt3gGJN0vJ1fZQoaAZoCWgPQwhOCvMeZ+dsQJSGlFKUaBVNKAFoFkdAm3fXlS0jT3V9lChoBmgJaA9DCLJ/ngYMHnBAlIaUUpRoFU09AWgWR0Cbd/4wyqMndX2UKGgGaAloD0MIZi5weazlSECUhpRSlGgVS/doFkdAm3lCQgcLjXV9lChoBmgJaA9DCEWDFDyFBkdAlIaUUpRoFUv3aBZHQJt5dCtzS1F1fZQoaAZoCWgPQwi8WBgiJ61xQJSGlFKUaBVNZQFoFkdAm3mwW3z+WHV9lChoBmgJaA9DCIdNZOYCYW5AlIaUUpRoFU1CAWgWR0Cbed/mDDjzdX2UKGgGaAloD0MI97AXCth+RECUhpRSlGgVS+5oFkdAm3pmKdhAnnV9lChoBmgJaA9DCM/Yl2w8l3BAlIaUUpRoFU10AWgWR0Cbem5vtMPCdX2UKGgGaAloD0MIwFq1awJyckCUhpRSlGgVTU4BaBZHQJt7MjHGS6l1fZQoaAZoCWgPQwgUQZyHk01vQJSGlFKUaBVNIQFoFkdAm3vyuZCv5nV9lChoBmgJaA9DCMjShy6oanJAlIaUUpRoFU03AWgWR0CbfHW7OE/TdX2UKGgGaAloD0MIezGUE21zbkCUhpRSlGgVTTYBaBZHQJt97fuTibV1fZQoaAZoCWgPQwjBxYoaTHRQQJSGlFKUaBVNBQFoFkdAm34xFuvU0HV9lChoBmgJaA9DCDONJhcjE3BAlIaUUpRoFU0aAWgWR0CbfpcL0BfbdX2UKGgGaAloD0MI61VkdMB2b0CUhpRSlGgVTTMBaBZHQJt+yp84Pwx1fZQoaAZoCWgPQwhQb0bN15JxQJSGlFKUaBVNTAFoFkdAm4FqG1x82XV9lChoBmgJaA9DCBgLQ+T07HBAlIaUUpRoFU1JAWgWR0CbgYGs3hn8dX2UKGgGaAloD0MIxNDq5MwzckCUhpRSlGgVTQ4BaBZHQJuBuIFeOXF1fZQoaAZoCWgPQwjn4QSmU1NrQJSGlFKUaBVNIQFoFkdAm4HakVN5+3V9lChoBmgJaA9DCC4dc54xC21AlIaUUpRoFU1wAWgWR0CbgjB3iaRZdX2UKGgGaAloD0MItJQsJ2GAcECUhpRSlGgVTTEBaBZHQJuCgfLcKw91fZQoaAZoCWgPQwi3Xz5ZcXlwQJSGlFKUaBVNSwFoFkdAm4LStA9mpXV9lChoBmgJaA9DCPDfvDix03FAlIaUUpRoFU0YAWgWR0Cbg24REnb7dX2UKGgGaAloD0MIV0Chnj7obECUhpRSlGgVTUUBaBZHQJuDz/DLr5Z1fZQoaAZoCWgPQwg/qIsUShJxQJSGlFKUaBVNTgFoFkdAm4QDENvwVnVlLg=="
|
74 |
+
},
|
75 |
+
"ep_success_buffer": {
|
76 |
+
":type:": "<class 'collections.deque'>",
|
77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
78 |
+
},
|
79 |
+
"_n_updates": 248,
|
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 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:00c0b692e9bb4b7536846c1261f5c3efa7b5899d24bfbce0aa3c41d09f931435
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f46840b7ae3e6a53505073f85cd61b9f0fc8f08f1f897c7aee8112047c987285
|
3 |
+
size 43393
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.9.16
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (206 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 244.68845041409423, "std_reward": 20.399995130013977, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-24T07:07:54.091272"}
|