Upload PPO LunarLander-v2 trained agent
Browse files- .gitattributes +1 -0
- README.md +37 -3
- 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 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
replay.mp4 filter=lfs diff=lfs merge=lfs -text
|
README.md
CHANGED
|
@@ -1,3 +1,37 @@
|
|
| 1 |
-
---
|
| 2 |
-
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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: 273.59 +/- 14.66
|
| 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 0x799f1981bba0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x799f1981bc40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x799f1981bce0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x799f1981bd80>", "_build": "<function ActorCriticPolicy._build at 0x799f1981be20>", "forward": "<function ActorCriticPolicy.forward at 0x799f1981bec0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x799f1981bf60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x799f19820040>", "_predict": "<function ActorCriticPolicy._predict at 0x799f198200e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x799f19820180>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x799f19820220>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x799f198202c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x799f2587b900>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1743412037303366908, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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 Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "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:bd646e272f681ea705eeb40bf8f929d0a4e3358d7fdedcc26960db8c45b12aab
|
| 3 |
+
size 148127
|
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 0x799f1981bba0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x799f1981bc40>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x799f1981bce0>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x799f1981bd80>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x799f1981be20>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x799f1981bec0>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x799f1981bf60>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x799f19820040>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x799f198200e0>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x799f19820180>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x799f19820220>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x799f198202c0>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x799f2587b900>"
|
| 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": 1743412037303366908,
|
| 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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
|
| 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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
|
| 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:c52971574621888cf25dbe44bcb94ac434024f2dfd02762d59ba415dcd1ffd43
|
| 3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7ed50960166c0fd00bdf83fce616ff79d9afd1a35de7b942d45e59d70a20f7f7
|
| 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 Thu Jun 27 21:05:47 UTC 2024
|
| 2 |
+
- Python: 3.11.11
|
| 3 |
+
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.6.0+cu124
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 2.0.2
|
| 7 |
+
- Cloudpickle: 3.1.1
|
| 8 |
+
- Gymnasium: 0.28.1
|
| 9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2bd50c96d39d0f2ef52359f3b106130f052fe7aa42ac93b37fdc7ffc6af11f27
|
| 3 |
+
size 142778
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 273.59052335740677, "std_reward": 14.656382945396913, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-31T09:45:01.452800"}
|