Commit ·
c3cc6ec
1
Parent(s): b4ea87a
Upload PPO LunarLander-v2 trained agent
Browse files- README.md +37 -0
- config.json +1 -0
- pp0-LunarLander-v2-anil2444.zip +3 -0
- pp0-LunarLander-v2-anil2444/_stable_baselines3_version +1 -0
- pp0-LunarLander-v2-anil2444/data +95 -0
- pp0-LunarLander-v2-anil2444/policy.optimizer.pth +3 -0
- pp0-LunarLander-v2-anil2444/policy.pth +3 -0
- pp0-LunarLander-v2-anil2444/pytorch_variables.pth +3 -0
- pp0-LunarLander-v2-anil2444/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: 282.25 +/- 13.25
|
| 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 0x7fc88b902550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc88b9025e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc88b902670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc88b902700>", "_build": "<function ActorCriticPolicy._build at 0x7fc88b902790>", "forward": "<function ActorCriticPolicy.forward at 0x7fc88b902820>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc88b9028b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc88b902940>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc88b9029d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc88b902a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc88b902af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc88b902b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc88b907140>"}, "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": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679729942571294748, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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": -0.007616000000000067, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 492, "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, "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"}}
|
pp0-LunarLander-v2-anil2444.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d3f1cda88e2fb24658f70eb0d1773d73c3c6dccd2c54ba05d197196c1ad7698a
|
| 3 |
+
size 147349
|
pp0-LunarLander-v2-anil2444/_stable_baselines3_version
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1.7.0
|
pp0-LunarLander-v2-anil2444/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 0x7fc88b902550>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc88b9025e0>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc88b902670>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc88b902700>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fc88b902790>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fc88b902820>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc88b9028b0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc88b902940>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fc88b9029d0>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc88b902a60>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc88b902af0>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc88b902b80>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7fc88b907140>"
|
| 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": 2015232,
|
| 47 |
+
"_total_timesteps": 2000000,
|
| 48 |
+
"_num_timesteps_at_start": 0,
|
| 49 |
+
"seed": null,
|
| 50 |
+
"action_noise": null,
|
| 51 |
+
"start_time": 1679729942571294748,
|
| 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": -0.007616000000000067,
|
| 71 |
+
"ep_info_buffer": {
|
| 72 |
+
":type:": "<class 'collections.deque'>",
|
| 73 |
+
":serialized:": "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"
|
| 74 |
+
},
|
| 75 |
+
"ep_success_buffer": {
|
| 76 |
+
":type:": "<class 'collections.deque'>",
|
| 77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
| 78 |
+
},
|
| 79 |
+
"_n_updates": 492,
|
| 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 |
+
}
|
pp0-LunarLander-v2-anil2444/policy.optimizer.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:62f3899a412b8a820380f96dc7c6dba2bc4264268bbfe63b13d825d620e8df77
|
| 3 |
+
size 87929
|
pp0-LunarLander-v2-anil2444/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9ea20724eb4a22be13fc1fba967624262e5aeb770be62a8af505cd62c4f45f6b
|
| 3 |
+
size 43393
|
pp0-LunarLander-v2-anil2444/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
| 3 |
+
size 431
|
pp0-LunarLander-v2-anil2444/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 (188 kB). View file
|
|
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 282.25259164354964, "std_reward": 13.247733829255518, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-25T08:30:20.537079"}
|