jmarinfi commited on
Commit
140297e
1 Parent(s): 567d19c

Upload PPO LunarLander-v2 trained agent

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 259.45 +/- 23.05
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 260.63 +/- 26.64
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 0x785b5abc5990>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x785b5abc5a20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x785b5abc5ab0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x785b5abc5b40>", "_build": "<function ActorCriticPolicy._build at 0x785b5abc5bd0>", "forward": "<function ActorCriticPolicy.forward at 0x785b5abc5c60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x785b5abc5cf0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x785b5abc5d80>", "_predict": "<function ActorCriticPolicy._predict at 0x785b5abc5e10>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x785b5abc5ea0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x785b5abc5f30>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x785b5abc5fc0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x785b5ad69bc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716429354728371040, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM1QfLwU7ui4fftZO5u9YjgYg5m7rLMKugAAgD8AAIA/QCSSvSmoJrqE1EI7logLNk2RUzvNXAM1AAAAAAAAgD/AEc69rj+Gunreozqattq0tAkWu7OPurkAAIA/AACAPzMpsTzwfLA/XSA4P2N6AL/DkaC8+brFvQAAAAAAAAAAI2J9vuQFaD9Lcqi+vYPXvno8mL61kpq8AAAAAAAAAADNWn687Mm/uekxMTsvs+c1jwiquhqhS7oAAIA/AACAPya2qL32hC26SjEWu1uebzjX+7I5+DWhOQAAgD8AAIA/jUWmvXGtRLmwg4k85cCwtmLZjjlmlKu1AAAAAAAAgD/mAN89rlOBug5hxjp+wqI1y/kGu6OW57kAAAAAAACAP7Ocyr3hBIy6NPkwu57oAzi6/7K6M83UOQAAgD8AAIA/mtMEvI8OMrqaJQo6ab1ctcyoRbs7iyC5AACAPwAAgD/zI7a9hbPTubPzezuz0La2bgCNu+W+k7oAAIA/AACAP4Bntj1cj3C6aoFGu+/cV7YBygq7SMnFNQAAgD8AAIA/ZpoRPMhvtT4JcCe+h/WYvrJ5w7vAA6G8AAAAAAAAAADNIke8KdAEurkDjbmpuBa1Ri6GugdbpTgAAIA/AACAP837ujzDsRe6tnEKuoUgh7bBz1G7JvwgOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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, "_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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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 Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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 0x7964bb74a830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7964bb74a8c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7964bb74a950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7964bb74a9e0>", "_build": "<function ActorCriticPolicy._build at 0x7964bb74aa70>", "forward": "<function ActorCriticPolicy.forward at 0x7964bb74ab00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7964bb74ab90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7964bb74ac20>", "_predict": "<function ActorCriticPolicy._predict at 0x7964bb74acb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7964bb74ad40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7964bb74add0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7964bb74ae60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7964bb6ecb80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1725473633833041786, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM1nX7324DS6KL+BOdZ0ojQYJ4U7glOZuAAAgD8AAIA/xqwGvrgJoLufVSC8EJRyuvQj8zzyn1A7AACAPwAAgD8zB+S8ChdoON9Ak7oBFB22dFSyO9dEsjkAAIA/AACAP2ZGTL3Pux28u3fZugEfjTzK9YI9jnNqvQAAgD8AAIA/ALusPIaVjD8uRDS8obK0vtvLPz0iPgy9AAAAAAAAAADNpM47XDs3urIVors7TjM18NxKO1B0o7QAAIA/AACAP03X1b1SgJO5mAzYOmb2wrMbRo+7bfcAugAAgD8AAIA/ZlahvI9+Rrrzzs66mrgstjIiujpGOvE5AACAPwAAgD8AgHw67GnUuQbpSzlR7Myz5JJIuh68b7gAAIA/AACAP4Bj/70UsNW6dvk5vPpoR7nMi2Q7ZkItOgAAgD8AAIA/gJBePRSYn7r9VDI6xm4aNTm7mzktX025AACAPwAAgD8zITa94cSMumbtTDpVMzE2WRxBO4pMbrkAAIA/AACAP4CnZL1In426W8JUuyGjezjXNG06ePwuOQAAgD8AAIA/zQOHvI/ec7q9zjS61WAgtRf6Srsun1M5AACAPwAAgD9m2uo7uJ62t6NtbbgBJYazUwzLO3qukTcAAIA/AACAPzNVC74cY2A97k8SPtEnU75mQ649ljo4PQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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, "_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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "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:d1ab1a8980ab4a06cf446a7f2009f04fb21bc5680f4bc4ec77503fd325da178e
3
- size 148080
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:787e09128f47cc3ca641241dbeb4cc5cd1dd580dab66601baf920f891b47629d
3
+ size 148076
ppo-LunarLander-v2/data CHANGED
@@ -4,20 +4,20 @@
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 0x785b5abc5990>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x785b5abc5a20>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x785b5abc5ab0>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x785b5abc5b40>",
11
- "_build": "<function ActorCriticPolicy._build at 0x785b5abc5bd0>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x785b5abc5c60>",
13
- "extract_features": "<function ActorCriticPolicy.extract_features at 0x785b5abc5cf0>",
14
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x785b5abc5d80>",
15
- "_predict": "<function ActorCriticPolicy._predict at 0x785b5abc5e10>",
16
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x785b5abc5ea0>",
17
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x785b5abc5f30>",
18
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x785b5abc5fc0>",
19
  "__abstractmethods__": "frozenset()",
20
- "_abc_impl": "<_abc._abc_data object at 0x785b5ad69bc0>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
@@ -26,12 +26,12 @@
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
- "start_time": 1716429354728371040,
30
  "learning_rate": 0.0003,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
34
- ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM1QfLwU7ui4fftZO5u9YjgYg5m7rLMKugAAgD8AAIA/QCSSvSmoJrqE1EI7logLNk2RUzvNXAM1AAAAAAAAgD/AEc69rj+Gunreozqattq0tAkWu7OPurkAAIA/AACAPzMpsTzwfLA/XSA4P2N6AL/DkaC8+brFvQAAAAAAAAAAI2J9vuQFaD9Lcqi+vYPXvno8mL61kpq8AAAAAAAAAADNWn687Mm/uekxMTsvs+c1jwiquhqhS7oAAIA/AACAPya2qL32hC26SjEWu1uebzjX+7I5+DWhOQAAgD8AAIA/jUWmvXGtRLmwg4k85cCwtmLZjjlmlKu1AAAAAAAAgD/mAN89rlOBug5hxjp+wqI1y/kGu6OW57kAAAAAAACAP7Ocyr3hBIy6NPkwu57oAzi6/7K6M83UOQAAgD8AAIA/mtMEvI8OMrqaJQo6ab1ctcyoRbs7iyC5AACAPwAAgD/zI7a9hbPTubPzezuz0La2bgCNu+W+k7oAAIA/AACAP4Bntj1cj3C6aoFGu+/cV7YBygq7SMnFNQAAgD8AAIA/ZpoRPMhvtT4JcCe+h/WYvrJ5w7vAA6G8AAAAAAAAAADNIke8KdAEurkDjbmpuBa1Ri6GugdbpTgAAIA/AACAP837ujzDsRe6tnEKuoUgh7bBz1G7JvwgOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
35
  },
36
  "_last_episode_starts": {
37
  ":type:": "<class 'numpy.ndarray'>",
@@ -45,7 +45,7 @@
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'>",
 
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 0x7964bb74a830>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7964bb74a8c0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7964bb74a950>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7964bb74a9e0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7964bb74aa70>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7964bb74ab00>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7964bb74ab90>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7964bb74ac20>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7964bb74acb0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7964bb74ad40>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7964bb74add0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7964bb74ae60>",
19
  "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7964bb6ecb80>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
 
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
+ "start_time": 1725473633833041786,
30
  "learning_rate": 0.0003,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM1nX7324DS6KL+BOdZ0ojQYJ4U7glOZuAAAgD8AAIA/xqwGvrgJoLufVSC8EJRyuvQj8zzyn1A7AACAPwAAgD8zB+S8ChdoON9Ak7oBFB22dFSyO9dEsjkAAIA/AACAP2ZGTL3Pux28u3fZugEfjTzK9YI9jnNqvQAAgD8AAIA/ALusPIaVjD8uRDS8obK0vtvLPz0iPgy9AAAAAAAAAADNpM47XDs3urIVors7TjM18NxKO1B0o7QAAIA/AACAP03X1b1SgJO5mAzYOmb2wrMbRo+7bfcAugAAgD8AAIA/ZlahvI9+Rrrzzs66mrgstjIiujpGOvE5AACAPwAAgD8AgHw67GnUuQbpSzlR7Myz5JJIuh68b7gAAIA/AACAP4Bj/70UsNW6dvk5vPpoR7nMi2Q7ZkItOgAAgD8AAIA/gJBePRSYn7r9VDI6xm4aNTm7mzktX025AACAPwAAgD8zITa94cSMumbtTDpVMzE2WRxBO4pMbrkAAIA/AACAP4CnZL1In426W8JUuyGjezjXNG06ePwuOQAAgD8AAIA/zQOHvI/ec7q9zjS61WAgtRf6Srsun1M5AACAPwAAgD9m2uo7uJ62t6NtbbgBJYazUwzLO3qukTcAAIA/AACAPzNVC74cY2A97k8SPtEnU75mQ649ljo4PQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
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'>",
ppo-LunarLander-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:1a556cc29a0273e4dc874a1beb8cc572ec3c90ea0a3ea7ececbe9a809c99ed81
3
  size 88362
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0ff796902c025afed3c6f36bd7011dbe566e5fb13ead4f600860ea767bb8c336
3
  size 88362
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3db03779c165f3039e6c1fc0cf9eace93ea4b212bb866c73ef7d0544e0bc5998
3
  size 43762
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b039b355eedc5203fd3efa9be37f0cbe59c6f3a94f52fd5b71c3c01f4d650dd8
3
  size 43762
ppo-LunarLander-v2/system_info.txt CHANGED
@@ -1,9 +1,9 @@
1
- - OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
2
  - Python: 3.10.12
3
  - Stable-Baselines3: 2.0.0a5
4
- - PyTorch: 2.3.0+cu121
5
  - GPU Enabled: True
6
- - Numpy: 1.25.2
7
  - Cloudpickle: 2.2.1
8
  - Gymnasium: 0.28.1
9
  - OpenAI Gym: 0.25.2
 
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: 3.10.12
3
  - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.4.0+cu121
5
  - GPU Enabled: True
6
+ - Numpy: 1.26.4
7
  - Cloudpickle: 2.2.1
8
  - Gymnasium: 0.28.1
9
  - OpenAI Gym: 0.25.2
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 259.45329751984394, "std_reward": 23.051987609386906, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-23T03:01:08.771568"}
 
1
+ {"mean_reward": 260.63196020000004, "std_reward": 26.640020325479874, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-04T19:27:26.940222"}