Upload second trained agent using PPO on LunarLander-v2
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2.zip +2 -2
- ppo-LunarLander-v2/data +18 -18
- ppo-LunarLander-v2/policy.optimizer.pth +2 -2
- 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: 259.12 +/- 21.34
|
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 0x7b5fcbe01000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b5fcbe01090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b5fcbe01120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b5fcbe011b0>", "_build": "<function ActorCriticPolicy._build at 0x7b5fcbe01240>", "forward": "<function ActorCriticPolicy.forward at 0x7b5fcbe012d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b5fcbe01360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b5fcbe013f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b5fcbe01480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b5fcbe01510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b5fcbe015a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b5fcbe01630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b5fcbdaa0c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710262090139389310, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAGYMYbw3cH0+wJB1PBPQRL6vBLS8MtCCPQAAAAAAAAAADRglvq/ibD+UwAS63unDvo/j3L0FY+a7AAAAAAAAAACa67K9nKoevNNMVzzUSCI9LRkWvYdtoLoAAAAAAAAAALN/tr327Gk9jyjEPYO0G75vfYu9FYnEvAAAAAAAAAAAMyb2vaQZpT71Z38+X3WCvkFhjj0A7l27AAAAAAAAAAAzc4A74dSauqIUUrqeU5G2v+/AuWuscjkAAIA/AACAP8a/Rr41Sno/aXawvn6BpL7S/o++9Y6hvAAAAAAAAAAAJiQoPlJCrj7MFy++M7qhvqNPN714do49AAAAAAAAAAAatgi99sVzvMaFADzDcpo81snWPX72eL0AAIA/AACAP+Vgjb6g2V8/mLD8vQx5s76GUoG+sFdpPAAAAAAAAAAAFcmSvkrXRj8C9YU9sO+3vvHFRr62LKk9AAAAAAAAAABmo/a8zjWRPxJBob3t5vC+T52mvF6fM70AAAAAAAAAAM3Ll7ycp1q8ZlwjPVbUwrzfIyi9Nn0fvgAAgD8AAIA/zWk3vWlgT7xUILY7sotXvauSETwewYk9AACAPwAAgD9mEx099HuoP7j/TD609Ou+T+yFPX5xJj4AAAAAAAAAAAAAwLpsgue7gV+ePPqMqjyVBcu7lruSuwAAgD8AAIA/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": 291, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.58+-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": "1.25.2", "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 0x7b5fcbe01000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b5fcbe01090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b5fcbe01120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b5fcbe011b0>", "_build": "<function ActorCriticPolicy._build at 0x7b5fcbe01240>", "forward": "<function ActorCriticPolicy.forward at 0x7b5fcbe012d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b5fcbe01360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b5fcbe013f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b5fcbe01480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b5fcbe01510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b5fcbe015a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b5fcbe01630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b5fcbdaa0c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710262090139389310, "learning_rate": 0.0, "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": 291, "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:": "gAWVxgEAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUtDQwRkAVMAlE5HAAAAAAAAAACGlCmMAV+UhZSMHzxpcHl0aG9uLWlucHV0LTIwLWNjNGY2MmUzYzI1ZD6UjAg8bGFtYmRhPpRLDUMCBACUKSl0lFKUfZQojAtfX3BhY2thZ2VfX5ROjAhfX25hbWVfX5SMCF9fbWFpbl9flHVOTk50lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaBZ9lH2UKGgTaA2MDF9fcXVhbG5hbWVfX5RoDYwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoFIwHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5ROjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": 16, "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": "1.25.2", "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:d615a9cce5978e06c9809330311453838bd02051b59ce5e8843c5ae4a713e945
|
3 |
+
size 147909
|
ppo-LunarLander-v2/data
CHANGED
@@ -27,7 +27,7 @@
|
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
"start_time": 1710262090139389310,
|
30 |
-
"learning_rate": 0.
|
31 |
"tensorboard_log": null,
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -52,6 +52,21 @@
|
|
52 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
},
|
54 |
"_n_updates": 291,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
55 |
"observation_space": {
|
56 |
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
":serialized:": "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",
|
@@ -69,7 +84,7 @@
|
|
69 |
},
|
70 |
"action_space": {
|
71 |
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
-
":serialized:": "
|
73 |
"n": "4",
|
74 |
"start": "0",
|
75 |
"_shape": [],
|
@@ -77,23 +92,8 @@
|
|
77 |
"_np_random": null
|
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,
|
87 |
-
"n_epochs": 4,
|
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 |
}
|
|
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
"start_time": 1710262090139389310,
|
30 |
+
"learning_rate": 0.0,
|
31 |
"tensorboard_log": null,
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
52 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
},
|
54 |
"_n_updates": 291,
|
55 |
+
"n_steps": 1024,
|
56 |
+
"gamma": 0.999,
|
57 |
+
"gae_lambda": 0.98,
|
58 |
+
"ent_coef": 0.01,
|
59 |
+
"vf_coef": 0.5,
|
60 |
+
"max_grad_norm": 0.5,
|
61 |
+
"batch_size": 64,
|
62 |
+
"n_epochs": 4,
|
63 |
+
"clip_range": {
|
64 |
+
":type:": "<class 'function'>",
|
65 |
+
":serialized:": "gAWVxgEAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUtDQwRkAVMAlE5HAAAAAAAAAACGlCmMAV+UhZSMHzxpcHl0aG9uLWlucHV0LTIwLWNjNGY2MmUzYzI1ZD6UjAg8bGFtYmRhPpRLDUMCBACUKSl0lFKUfZQojAtfX3BhY2thZ2VfX5ROjAhfX25hbWVfX5SMCF9fbWFpbl9flHVOTk50lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaBZ9lH2UKGgTaA2MDF9fcXVhbG5hbWVfX5RoDYwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoFIwHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5ROjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
66 |
+
},
|
67 |
+
"clip_range_vf": null,
|
68 |
+
"normalize_advantage": true,
|
69 |
+
"target_kl": null,
|
70 |
"observation_space": {
|
71 |
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
72 |
":serialized:": "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",
|
|
|
84 |
},
|
85 |
"action_space": {
|
86 |
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
87 |
+
":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
88 |
"n": "4",
|
89 |
"start": "0",
|
90 |
"_shape": [],
|
|
|
92 |
"_np_random": null
|
93 |
},
|
94 |
"n_envs": 16,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
95 |
"lr_schedule": {
|
96 |
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
}
|
99 |
}
|
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
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a8fbaa1284ee2d6d00c46e91f4370f747c14a41d754c35858f549d15f7adba8a
|
3 |
+
size 88490
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 259.1244306, "std_reward": 21.338845756469492, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-12T17:30:21.869030"}
|