Uploaded LunarLander-v2 model
Browse files- README.md +37 -0
- config.json +1 -0
- replay.mp4 +0 -0
- results.json +1 -0
- testing.zip +3 -0
- testing/_stable_baselines3_version +1 -0
- testing/data +94 -0
- testing/policy.optimizer.pth +3 -0
- testing/policy.pth +3 -0
- testing/pytorch_variables.pth +3 -0
- testing/system_info.txt +7 -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: 240.44 +/- 25.14
|
| 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 0x7f56c27f1ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f56c27f1d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f56c27f1dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f56c27f1e50>", "_build": "<function ActorCriticPolicy._build at 0x7f56c27f1ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f56c27f1f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f56c27f5040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f56c27f50d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f56c27f5160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f56c27f51f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f56c27f5280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f56c27ed4b0>"}, "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": 1671249801176931796, "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:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 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"}}
|
replay.mp4
ADDED
|
Binary file (254 kB). View file
|
|
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 240.4372912266333, "std_reward": 25.139465354919505, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-17T04:29:45.231260"}
|
testing.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8e549bb73b9886fc796bdaa6bb46dc05487ceb379ef7e2465087001eb2112e37
|
| 3 |
+
size 147214
|
testing/_stable_baselines3_version
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1.6.2
|
testing/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 0x7f56c27f1ca0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f56c27f1d30>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f56c27f1dc0>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f56c27f1e50>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f56c27f1ee0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f56c27f1f70>",
|
| 13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f56c27f5040>",
|
| 14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f56c27f50d0>",
|
| 15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f56c27f5160>",
|
| 16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f56c27f51f0>",
|
| 17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f56c27f5280>",
|
| 18 |
+
"__abstractmethods__": "frozenset()",
|
| 19 |
+
"_abc_impl": "<_abc_data object at 0x7f56c27ed4b0>"
|
| 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": 1015808,
|
| 46 |
+
"_total_timesteps": 1000000,
|
| 47 |
+
"_num_timesteps_at_start": 0,
|
| 48 |
+
"seed": null,
|
| 49 |
+
"action_noise": null,
|
| 50 |
+
"start_time": 1671249801176931796,
|
| 51 |
+
"learning_rate": 0.0003,
|
| 52 |
+
"tensorboard_log": null,
|
| 53 |
+
"lr_schedule": {
|
| 54 |
+
":type:": "<class 'function'>",
|
| 55 |
+
":serialized:": "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"
|
| 56 |
+
},
|
| 57 |
+
"_last_obs": {
|
| 58 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 59 |
+
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAP1orj7MEwc/abCVvoSiLL4jCiQ9zTihvAAAAAAAAAAAADS2Oz2RJrvOxL27Al9/PGyYejxiiF29AACAPwAAgD+aRdY82eO1P9KjJD8OHJU9KeaavAVdAL0AAAAAAAAAADPp172PBli6mNJeOiCVOzV6pMA50ieDuQAAAAAAAIA/jcBxPhV8nT510R2+Sj0QvpLM1jwHdZy9AAAAAAAAAAAzcxS7FNyduqPY6zr5EBg2301Wtwj1B7oAAIA/AACAP4BWFT1VjO8+Fy2nvTxPh75xsyy9ay+JvQAAAAAAAAAArTxyvgTy6j5C5ls+Ey5yvi7xtbvzz9o8AAAAAAAAAACajZm9KboEPxWxCz5cgAu+JCsUPASKjj0AAAAAAAAAAJrym7x3uEw/WDJ/uq2ym76na0G9LWIJPAAAAAAAAAAAGlaJvRDilj7y9hk9R5pYvmSKJLw9RE47AAAAAAAAAACzXjy94ay5ur4Ph7VRPEaw7cn2OBTYsDQAAIA/AACAP5oRr717CpO6SifMOS8iFzZPQ8w6WpjsuAAAAAAAAIA/Jo+QvWn+Nz2WWGM9UqdFvl3Mj7pYElq7AAAAAAAAAABmQdO9y5zPPQ75Rj4dtEK+czUePRWAZD0AAAAAAAAAABNIFb7P4ws/joxCPYeaab6WNSG9i+xjPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
|
| 60 |
+
},
|
| 61 |
+
"_last_episode_starts": {
|
| 62 |
+
":type:": "<class 'numpy.ndarray'>",
|
| 63 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": -0.015808000000000044,
|
| 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": 248,
|
| 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": 4,
|
| 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 |
+
}
|
testing/policy.optimizer.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:83548919173fd6ab453a03184be354679650cdd28f3be84fe91ae4e07cad6db8
|
| 3 |
+
size 87929
|
testing/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c6cc59d6a9b81108813aed47d0fcc27701156c5ea4be651832c8899f52963eae
|
| 3 |
+
size 43201
|
testing/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
| 3 |
+
size 431
|
testing/system_info.txt
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 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
|