IAmAIReally
commited on
Commit
·
00e9ea3
1
Parent(s):
60f2730
first try
Browse files- README.md +1 -1
- config.json +1 -1
- first try.zip +3 -0
- first try/_stable_baselines3_version +1 -0
- first try/data +99 -0
- first try/policy.optimizer.pth +3 -0
- first try/policy.pth +3 -0
- first try/pytorch_variables.pth +3 -0
- first try/system_info.txt +9 -0
- 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: 270.43 +/- 22.27
|
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 0x7ae6da8ce3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ae6da8ce440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ae6da8ce4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ae6da8ce560>", "_build": "<function ActorCriticPolicy._build at 0x7ae6da8ce5f0>", "forward": "<function ActorCriticPolicy.forward at 0x7ae6da8ce680>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ae6da8ce710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ae6da8ce7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ae6da8ce830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ae6da8ce8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ae6da8ce950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ae6da8ce9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ae6da8731c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1697270924749745851, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 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 0x7eaee9a2a830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7eaee9a2a8c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7eaee9a2a950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7eaee9a2a9e0>", "_build": "<function ActorCriticPolicy._build at 0x7eaee9a2aa70>", "forward": "<function ActorCriticPolicy.forward at 0x7eaee9a2ab00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7eaee9a2ab90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7eaee9a2ac20>", "_predict": "<function ActorCriticPolicy._predict at 0x7eaee9a2acb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7eaee9a2ad40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7eaee9a2add0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7eaee9a2ae60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7eaee9a2d100>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1697291487391119578, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "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": 8, "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 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"}}
|
first try.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0081ac237bc6f4f7af1e742abb0409062ab8f1e0ff2405e07737eca126222986
|
3 |
+
size 146743
|
first try/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
first try/data
ADDED
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 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 0x7eaee9a2a830>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7eaee9a2a8c0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7eaee9a2a950>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7eaee9a2a9e0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7eaee9a2aa70>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7eaee9a2ab00>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7eaee9a2ab90>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7eaee9a2ac20>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7eaee9a2acb0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7eaee9a2ad40>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7eaee9a2add0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7eaee9a2ae60>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7eaee9a2d100>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1697291487391119578,
|
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'>",
|
38 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -0.015808000000000044,
|
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": 248,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "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",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": null
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
80 |
+
"n_steps": 2048,
|
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,
|
87 |
+
"n_epochs": 8,
|
88 |
+
"clip_range": {
|
89 |
+
":type:": "<class 'function'>",
|
90 |
+
":serialized:": "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"
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null,
|
95 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
+
}
|
99 |
+
}
|
first try/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3bf98083de71432ea22e47f534c9343046467aa2af22a91a4a94abb0293c6a6b
|
3 |
+
size 87929
|
first try/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e1f42914cc2c16ef08423c98d3f2a06734a608076f4a0072d66206d0b634e6a5
|
3 |
+
size 43329
|
first try/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
first try/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.0.1+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.23.5
|
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":
|
|
|
1 |
+
{"mean_reward": 270.4334964, "std_reward": 22.268292463499833, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-14T14:19:34.773864"}
|