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 +94 -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: 306.58 +/- 10.86
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f255046f040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f255046f0d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f255046f160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f255046f1f0>", "_build": "<function ActorCriticPolicy._build at 0x7f255046f280>", "forward": "<function ActorCriticPolicy.forward at 0x7f255046f310>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f255046f3a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f255046f430>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f255046f4c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f255046f550>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f255046f5e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f25504694b0>"}, "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": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673345544582370116, "learning_rate": 0.0001, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAEAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3060, "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": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.27 #1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "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:dd53fc70f71d85ec2ba99627108a07664c3900c78ea85814697dc4c447dcfe6d
|
3 |
+
size 147089
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f255046f040>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f255046f0d0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f255046f160>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f255046f1f0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f255046f280>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f255046f310>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f255046f3a0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f255046f430>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f255046f4c0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f255046f550>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f255046f5e0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f25504694b0>"
|
20 |
+
},
|
21 |
+
"verbose": 1,
|
22 |
+
"policy_kwargs": {},
|
23 |
+
"observation_space": {
|
24 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
25 |
+
":serialized:": "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",
|
26 |
+
"dtype": "float32",
|
27 |
+
"_shape": [
|
28 |
+
8
|
29 |
+
],
|
30 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
31 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
32 |
+
"bounded_below": "[False False False False False False False False]",
|
33 |
+
"bounded_above": "[False False False False False False False False]",
|
34 |
+
"_np_random": null
|
35 |
+
},
|
36 |
+
"action_space": {
|
37 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
38 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
39 |
+
"n": 4,
|
40 |
+
"_shape": [],
|
41 |
+
"dtype": "int64",
|
42 |
+
"_np_random": null
|
43 |
+
},
|
44 |
+
"n_envs": 16,
|
45 |
+
"num_timesteps": 5013504,
|
46 |
+
"_total_timesteps": 5000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1673345544582370116,
|
51 |
+
"learning_rate": 0.0001,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/Gjbi6xxDLYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
|
56 |
+
},
|
57 |
+
"_last_obs": {
|
58 |
+
":type:": "<class 'numpy.ndarray'>",
|
59 |
+
":serialized:": "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"
|
60 |
+
},
|
61 |
+
"_last_episode_starts": {
|
62 |
+
":type:": "<class 'numpy.ndarray'>",
|
63 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAEAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.0027007999999999477,
|
70 |
+
"ep_info_buffer": {
|
71 |
+
":type:": "<class 'collections.deque'>",
|
72 |
+
":serialized:": "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"
|
73 |
+
},
|
74 |
+
"ep_success_buffer": {
|
75 |
+
":type:": "<class 'collections.deque'>",
|
76 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
+
},
|
78 |
+
"_n_updates": 3060,
|
79 |
+
"n_steps": 1024,
|
80 |
+
"gamma": 0.999,
|
81 |
+
"gae_lambda": 0.98,
|
82 |
+
"ent_coef": 0.01,
|
83 |
+
"vf_coef": 0.5,
|
84 |
+
"max_grad_norm": 0.5,
|
85 |
+
"batch_size": 64,
|
86 |
+
"n_epochs": 10,
|
87 |
+
"clip_range": {
|
88 |
+
":type:": "<class 'function'>",
|
89 |
+
":serialized:": "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"
|
90 |
+
},
|
91 |
+
"clip_range_vf": null,
|
92 |
+
"normalize_advantage": true,
|
93 |
+
"target_kl": null
|
94 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ee9d38a47d97d6b4e85bb27b3a2d7cac60cbe2c092a7953f450572031ecf94bb
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2a399ac379425521b4338440bb07d64120cd2f6e98df3ac653f0a15d4a8fe328
|
3 |
+
size 43201
|
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-glibc2.27 #1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
Python: 3.8.16
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cu116
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (180 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 306.57844296340147, "std_reward": 10.85612106220577, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-10T11:57:30.609528"}
|