maavaneck commited on
Commit
d63891a
·
verified ·
1 Parent(s): a1e8405

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: 255.68 +/- 25.23
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 266.69 +/- 21.79
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 0x7bc0e58ce7a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bc0e58ce830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bc0e58ce8c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bc0e58ce950>", "_build": "<function ActorCriticPolicy._build at 0x7bc0e58ce9e0>", "forward": "<function ActorCriticPolicy.forward at 0x7bc0e58cea70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bc0e58ceb00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bc0e58ceb90>", "_predict": "<function ActorCriticPolicy._predict at 0x7bc0e58cec20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bc0e58cecb0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bc0e58ced40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bc0e58cedd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bc0e5a5c240>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1721198840284798017, "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:": "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": "2.3.0+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 0x7bba98876680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bba98876710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bba988767a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bba98876830>", "_build": "<function ActorCriticPolicy._build at 0x7bba988768c0>", "forward": "<function ActorCriticPolicy.forward at 0x7bba98876950>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bba988769e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bba98876a70>", "_predict": "<function ActorCriticPolicy._predict at 0x7bba98876b00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bba98876b90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bba98876c20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bba98876cb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bba435b0680>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1727348268885172137, "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:": "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": "2.4.1+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:d34d66a87b68b228fbf8da7ada41d69ebc627a9aeedb11adf0f582917eb64336
3
- size 148084
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7dbb74f30ee1b166dc5482211f35d33fbb4e4a0eb3fea5a2d934a6059a33426b
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 0x7bc0e58ce7a0>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bc0e58ce830>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bc0e58ce8c0>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bc0e58ce950>",
11
- "_build": "<function ActorCriticPolicy._build at 0x7bc0e58ce9e0>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x7bc0e58cea70>",
13
- "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bc0e58ceb00>",
14
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bc0e58ceb90>",
15
- "_predict": "<function ActorCriticPolicy._predict at 0x7bc0e58cec20>",
16
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bc0e58cecb0>",
17
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bc0e58ced40>",
18
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bc0e58cedd0>",
19
  "__abstractmethods__": "frozenset()",
20
- "_abc_impl": "<_abc._abc_data object at 0x7bc0e5a5c240>"
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": 1721198840284798017,
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'>",
@@ -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 0x7bba98876680>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bba98876710>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bba988767a0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bba98876830>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7bba988768c0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7bba98876950>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bba988769e0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bba98876a70>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7bba98876b00>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bba98876b90>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bba98876c20>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bba98876cb0>",
19
  "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7bba435b0680>"
21
  },
22
  "verbose": 1,
23
  "policy_kwargs": {},
 
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
+ "start_time": 1727348268885172137,
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'>",
 
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:f671dbbeb806eda8668bfe62a1387a2b5b89296323a36db3c6da0e13c3ad279c
3
  size 88362
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:81648125d2b27d376f1581805d520f35797d138896fd85e0498822285ffdfa10
3
  size 88362
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:254cc17d6b11120c9d13261f58d2dad9d27e3db830e6ecca7f88d14836ae3def
3
  size 43762
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:294e7bab9cf0b63f7aa4cbdf5fd262a34a56a9119fbfa4be1c308f12698a0856
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 Thu Jun 27 21:05:47 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: 2.4.1+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": 255.67503769550495, "std_reward": 25.225103574396652, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-07-17T07:16:35.458993"}
 
1
+ {"mean_reward": 266.68630171167905, "std_reward": 21.785470540517647, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-26T11:19:28.834092"}