torkable commited on
Commit
7183ca1
1 Parent(s): 284e2e5

drive that shit better

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: MountainCar-v0
17
  metrics:
18
  - type: mean_reward
19
- value: -200.00 +/- 0.00
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: MountainCar-v0
17
  metrics:
18
  - type: mean_reward
19
+ value: -117.00 +/- 2.49
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 0x7b2f1d90b760>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2f1d90b7f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2f1d90b880>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2f1d90b910>", "_build": "<function ActorCriticPolicy._build at 0x7b2f1d90b9a0>", "forward": "<function ActorCriticPolicy.forward at 0x7b2f1d90ba30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2f1d90bac0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2f1d90bb50>", "_predict": "<function ActorCriticPolicy._predict at 0x7b2f1d90bbe0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2f1d90bc70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2f1d90bd00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2f1d90bd90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b2f24253a00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1694988898307458575, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAANJF/b7Vie27JHklv2KMyzuhJxm/VCBSO4cKw75TpkE8QzATv0ozLLyoGwe/MFYiuobf1b6Z8467nSIMvxxt9rvnJgq/2Q0HvEHnDL+r1oa7UcIVv1OXqrsW4fS+LsVWvIQt4b5xdkE8G9/9vqTFkjuP+gK//gAROsJCyb7KqLw7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_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]", "bounded_above": "[ True True]", "_shape": [2], "low": "[-1.2 -0.07]", "high": "[0.6 0.07]", "low_repr": "[-1.2 -0.07]", "high_repr": "[0.6 0.07]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIAwAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "3", "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "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 0x7b2f1d90b760>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2f1d90b7f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2f1d90b880>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2f1d90b910>", "_build": "<function ActorCriticPolicy._build at 0x7b2f1d90b9a0>", "forward": "<function ActorCriticPolicy.forward at 0x7b2f1d90ba30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2f1d90bac0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2f1d90bb50>", "_predict": "<function ActorCriticPolicy._predict at 0x7b2f1d90bbe0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2f1d90bc70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2f1d90bd00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2f1d90bd90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b2f24253a00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1694990367764562029, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAPvQlb/O6Vq9nt8WvwAAAACFne++klu6O6cqzr1KNzS94/p6vwEmGD21AIO+yZqAvOg64z2GAiY93mGhvnUDs7s/TgS/aYtSO16VhL56H648baZPv2Q2AL1J3yK/vs1qPKAtar84g288YuD2vhCzojzNkDW/iwVGOwP0Mr8iHFs8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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]", "bounded_above": "[ True True]", "_shape": [2], "low": "[-1.2 -0.07]", "high": "[0.6 0.07]", "low_repr": "[-1.2 -0.07]", "high_repr": "[0.6 0.07]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIAwAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "3", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.98, "gae_lambda": 0.98, "ent_coef": 0.05, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
mountain-car-v0.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:35db79702e6a73e8f3294ff8cec4bd60eb960730d4cbcc2a886bd237851e3dd5
3
- size 135470
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:173ae4f09c06cc75fb8f3366385dbc89aaf2f8b6081654c516f6121e305b299a
3
+ size 135469
mountain-car-v0/data CHANGED
@@ -26,16 +26,16 @@
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
- "start_time": 1694988898307458575,
30
  "learning_rate": 0.0003,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
34
- ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAANJF/b7Vie27JHklv2KMyzuhJxm/VCBSO4cKw75TpkE8QzATv0ozLLyoGwe/MFYiuobf1b6Z8467nSIMvxxt9rvnJgq/2Q0HvEHnDL+r1oa7UcIVv1OXqrsW4fS+LsVWvIQt4b5xdkE8G9/9vqTFkjuP+gK//gAROsJCyb7KqLw7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="
35
  },
36
  "_last_episode_starts": {
37
  ":type:": "<class 'numpy.ndarray'>",
38
- ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
  },
40
  "_last_original_obs": null,
41
  "_episode_num": 0,
@@ -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'>",
@@ -78,9 +78,9 @@
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,
 
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
+ "start_time": 1694990367764562029,
30
  "learning_rate": 0.0003,
31
  "tensorboard_log": null,
32
  "_last_obs": {
33
  ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAPvQlb/O6Vq9nt8WvwAAAACFne++klu6O6cqzr1KNzS94/p6vwEmGD21AIO+yZqAvOg64z2GAiY93mGhvnUDs7s/TgS/aYtSO16VhL56H648baZPv2Q2AL1J3yK/vs1qPKAtar84g288YuD2vhCzojzNkDW/iwVGOwP0Mr8iHFs8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="
35
  },
36
  "_last_episode_starts": {
37
  ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
  },
40
  "_last_original_obs": null,
41
  "_episode_num": 0,
 
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'>",
 
78
  },
79
  "n_envs": 16,
80
  "n_steps": 1024,
81
+ "gamma": 0.98,
82
  "gae_lambda": 0.98,
83
+ "ent_coef": 0.05,
84
  "vf_coef": 0.5,
85
  "max_grad_norm": 0.5,
86
  "batch_size": 64,
mountain-car-v0/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:32c07cb89d1cb793204a4f67e8176807e673c6bccdee97bc6d06969bf1a427ce
3
  size 81273
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dfc03738cae9045f65d99447a1eb89970869c9975c5096d33aa5720fac15a70d
3
  size 81273
mountain-car-v0/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e161bae4023ac259e3db6688e845672c980625312e1fa60556afbd2543484100
3
  size 40001
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7fc13119f005e64218bb7ad5974a79e1a0563167d3c67569131e8f4b60a90155
3
  size 40001
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -200.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-09-17T22:23:05.467331"}
 
1
+ {"mean_reward": -117.0, "std_reward": 2.4899799195977463, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-09-17T22:47:22.657271"}