LunarLander improved
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2.zip +2 -2
- ppo-LunarLander-v2/data +4 -4
- ppo-LunarLander-v2/policy.optimizer.pth +1 -1
- ppo-LunarLander-v2/policy.pth +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value:
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: 274.30 +/- 19.29
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
config.json
CHANGED
@@ -1 +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 0x7d7aea795e10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d7aea795ea0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d7aea795f30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d7aea795fc0>", "_build": "<function ActorCriticPolicy._build at 0x7d7aea796050>", "forward": "<function ActorCriticPolicy.forward at 0x7d7aea7960e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d7aea796170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d7aea796200>", "_predict": "<function ActorCriticPolicy._predict at 0x7d7aea796290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d7aea796320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d7aea7963b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d7aea796440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d7af17a0e00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100352, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1705032523010446447, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAOZ9NT1PVBq8/oNsvaogg74TTAC8tSjPvAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 4380, "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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
|
|
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 0x7d7aea795e10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d7aea795ea0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d7aea795f30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d7aea795fc0>", "_build": "<function ActorCriticPolicy._build at 0x7d7aea796050>", "forward": "<function ActorCriticPolicy.forward at 0x7d7aea7960e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d7aea796170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d7aea796200>", "_predict": "<function ActorCriticPolicy._predict at 0x7d7aea796290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d7aea796320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d7aea7963b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d7aea796440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d7af17a0e00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100352, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1705033308968144104, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAALZFW76VNVw/bmnMvsT3DL/denS+KxbrvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 4772, "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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d4d34a64d82d589469b51b9a9d904de4de08985351a801c32e75003ca082f277
|
3 |
+
size 147575
|
ppo-LunarLander-v2/data
CHANGED
@@ -26,12 +26,12 @@
|
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
-
"start_time":
|
30 |
"learning_rate": 0.0003,
|
31 |
"tensorboard_log": null,
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
34 |
-
":serialized:": "
|
35 |
},
|
36 |
"_last_episode_starts": {
|
37 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -45,13 +45,13 @@
|
|
45 |
"_stats_window_size": 100,
|
46 |
"ep_info_buffer": {
|
47 |
":type:": "<class 'collections.deque'>",
|
48 |
-
":serialized:": "
|
49 |
},
|
50 |
"ep_success_buffer": {
|
51 |
":type:": "<class 'collections.deque'>",
|
52 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
},
|
54 |
-
"_n_updates":
|
55 |
"n_steps": 1024,
|
56 |
"gamma": 0.999,
|
57 |
"gae_lambda": 0.98,
|
|
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
+
"start_time": 1705033308968144104,
|
30 |
"learning_rate": 0.0003,
|
31 |
"tensorboard_log": null,
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAALZFW76VNVw/bmnMvsT3DL/denS+KxbrvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
35 |
},
|
36 |
"_last_episode_starts": {
|
37 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
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": 4772,
|
55 |
"n_steps": 1024,
|
56 |
"gamma": 0.999,
|
57 |
"gae_lambda": 0.98,
|
ppo-LunarLander-v2/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 88490
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3ee6738a09d5891fe7b86e7b50e66250852210e0bd47417891cb0b24415c15b0
|
3 |
size 88490
|
ppo-LunarLander-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 43762
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f7a01edfaf2996e7f67aebeca95283fa0880883e9e4f2e3ea9de1ad3f6bd6e65
|
3 |
size 43762
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 274.2981086399467, "std_reward": 19.286705049467525, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-01-12T04:25:32.419560"}
|