Trained for more steps
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v3.zip +3 -0
- ppo-LunarLander-v3/_stable_baselines3_version +1 -0
- ppo-LunarLander-v3/data +99 -0
- ppo-LunarLander-v3/policy.optimizer.pth +3 -0
- ppo-LunarLander-v3/policy.pth +3 -0
- ppo-LunarLander-v3/pytorch_variables.pth +3 -0
- ppo-LunarLander-v3/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: 294.96 +/- 15.68
|
| 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 0x79267763e3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79267763e440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79267763e4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79267763e560>", "_build": "<function ActorCriticPolicy._build at 0x79267763e5f0>", "forward": "<function ActorCriticPolicy.forward at 0x79267763e680>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79267763e710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79267763e7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x79267763e830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79267763e8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79267763e950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79267763e9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x792619b37980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1731868786099857832, "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:": "gAWVQAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGMVwnhKlHmMAWyUTegDjAF0lEdAk9CShakhzXV9lChoBkdAZUQHkcS5AmgHTegDaAhHQJPRFO45Lh91fZQoaAZHQGIlWVeKKpFoB03oA2gIR0CT3eLMLWqcdX2UKGgGR0BaG9I9TxXoaAdN6ANoCEdAk+CkdFOO83V9lChoBkdAYyg8fV7QcGgHTegDaAhHQJPhdAzHjp91fZQoaAZHQGYsHbRF7UpoB03oA2gIR0CT5ld+G47SdX2UKGgGR0BiQkH+qBEsaAdN6ANoCEdAk/asMd92HXV9lChoBkdAZ2XtDUmUn2gHTegDaAhHQJP32QV9F4N1fZQoaAZHQGEdqZtvXK9oB03oA2gIR0CT+MR9PUKBdX2UKGgGR0Bkvt3ljmSyaAdN6ANoCEdAk/t+jRD1G3V9lChoBkdAYnJtYSxqwmgHTegDaAhHQJP/yq+8Gs51fZQoaAZHQGIPFI/Z/TdoB03oA2gIR0CUF6SE12q2dX2UKGgGR0BmMJvaURnOaAdN6ANoCEdAlBeiuEEkjXV9lChoBkdAZe2WTHKfWmgHTegDaAhHQJQZAl8gIQh1fZQoaAZHQGcnCHymQ8xoB03oA2gIR0CUGz9lEqlQdX2UKGgGR0BhFUOPNmlJaAdN6ANoCEdAlBufLxI8Q3V9lChoBkdAY1G4Ia99MWgHTegDaAhHQJQgylabF0h1fZQoaAZHv8ynrIHTqjdoB0v/aAhHQJQg8eMhouh1fZQoaAZHQF0JEoOQQtloB03oA2gIR0CUIUnaFmFrdX2UKGgGR0BlAw8IRh+faAdN6ANoCEdAlCxX6qKgqXV9lChoBkdAXsbIjnmq52gHTegDaAhHQJQuZoJzDGd1fZQoaAZHQGSSDm8ujAVoB03oA2gIR0CULwmiQDFIdX2UKGgGR0BjtTTQVsUJaAdN6ANoCEdAlDMqFZgXuXV9lChoBkdAYBViMo+fRWgHTegDaAhHQJRG9D0Dlo11fZQoaAZHQGP+pD3M6iloB03oA2gIR0CUSOUgSvkjdX2UKGgGR0BjEkV58jRlaAdN6ANoCEdAlEobZWaMJnV9lChoBkdAZsqNlRP422gHTegDaAhHQJRNNbC79Q51fZQoaAZHQGc/9SuQp4NoB03oA2gIR0CUZ153C9AYdX2UKGgGR0Bh0h2wFC9iaAdN6ANoCEdAlGdd4qwyI3V9lChoBkdAaKylsP8Q7WgHTegDaAhHQJRo/K0UoKF1fZQoaAZHQGLk7T+ee4FoB03oA2gIR0CUa2Zv1lGxdX2UKGgGR0Bi0BPAO8TSaAdN6ANoCEdAlGvbGrCFbnV9lChoBkdAZmhX9R77bmgHTegDaAhHQJRxK2JBPbh1fZQoaAZHQGMKASWZ7XxoB03oA2gIR0CUcVKdQO4HdX2UKGgGR0BcU8Nc4YJmaAdN6ANoCEdAlHHIZ62OQ3V9lChoBkdAX/A1AJLM92gHTegDaAhHQJR/nJwKjSJ1fZQoaAZHQGIJMeXAuZloB03oA2gIR0CUgV3VkMCtdX2UKGgGR0Bu7C55JK8MaAdNdQJoCEdAlIGeWBz3iHV9lChoBkdAXYPAqNIbwWgHTegDaAhHQJSB4Xdj5Kx1fZQoaAZHQGObEb5uZThoB03oA2gIR0CUhTxqwhW6dX2UKGgGR0BnKgxJul41aAdN6ANoCEdAlJJtN8E3bXV9lChoBkdAYUSjDbah6GgHTegDaAhHQJSTg2BJ7LN1fZQoaAZHQGL5OSW7e2xoB03oA2gIR0CUlyBcAzYVdX2UKGgGR0ByHpxCIDYAaAdNCAJoCEdAlJqM/IKc/nV9lChoBkdAXOo1yeZof2gHTegDaAhHQJSzLgxagVZ1fZQoaAZHQGUVVeSjgydoB03oA2gIR0CUsy3g1m8NdX2UKGgGR0Bnl+/FirksaAdN6ANoCEdAlLSBusLfDXV9lChoBkdAPYzrNW2gF2gHTRIBaAhHQJS1KX3QD3d1fZQoaAZHQGU9moaUA1hoB03oA2gIR0CUtpGlANXpdX2UKGgGR0Bn23uJDVpcaAdN6ANoCEdAlLbqAjIJaHV9lChoBkdAQW/acqe9SWgHS/1oCEdAlLfzc/MW43V9lChoBkdAaHX/c32mHmgHTegDaAhHQJS7bHCGetl1fZQoaAZHQGZ5K6WgOBloB03oA2gIR0CUu5CbtqpMdX2UKGgGR0BlrTgbZOBUaAdN6ANoCEdAlLvbgjyFwnV9lChoBkdAYqq5o4+8oWgHTegDaAhHQJTIKkl/pdN1fZQoaAZHQGWh9/rjYI1oB03oA2gIR0CUyH4HoouxdX2UKGgGR0BijJg7YChfaAdN6ANoCEdAlMjNoFmnO3V9lChoBkdAN0IsunMt9WgHS/loCEdAlMk3Fo+OfnV9lChoBkdAYfjbjcVQAWgHTegDaAhHQJTMsebNKRN1fZQoaAZHQGdWH7gsK9hoB03oA2gIR0CU3mt4iX6ZdX2UKGgGR0BkdbBInSfEaAdN6ANoCEdAlOj3tKIznHV9lChoBkdAY4wM3IdU82gHTegDaAhHQJTuYG1QZXN1fZQoaAZHQGatFpGnXNFoB03oA2gIR0CU7mEfDDTCdX2UKGgGR0BlxOOGTLW7aAdN6ANoCEdAlQHTAWSEDnV9lChoBkdASsMU21lXimgHS/hoCEdAlQJBri2lVXV9lChoBkdAYEXL8rI5pGgHTegDaAhHQJUCkq7ROUN1fZQoaAZHQHBxtHc1wYNoB01/AmgIR0CVBA1fVqetdX2UKGgGR0Bh1JClabF1aAdN6ANoCEdAlQQp8OTaCnV9lChoBkdAZNbRYRujymgHTegDaAhHQJUEh4Y77sR1fZQoaAZHQGLj12A5JbtoB03oA2gIR0CVBYgEU0vXdX2UKGgGR0BkYpJ/XoTxaAdN6ANoCEdAlQi32AXl83V9lChoBkdAYpIx1PnB+GgHTegDaAhHQJUI3Y02tMh1fZQoaAZHQHBzDdk8RthoB002A2gIR0CVDEeMQ2/BdX2UKGgGR0BirZCdBjWkaAdN6ANoCEdAlRhosmOU+3V9lChoBkdAYNZqY7aIvmgHTegDaAhHQJUZCkqMFU11fZQoaAZHQGL/jB2wFC9oB03oA2gIR0CVHS/H5rP/dX2UKGgGR0Bj4lGd7OVxaAdN6ANoCEdAlTX59/jKgnV9lChoBkdAZspTefqX4WgHTegDaAhHQJU68tcv/R51fZQoaAZHQGbRqaw2VFBoB03oA2gIR0CVOvLv1DjSdX2UKGgGR0BhRGii7CizaAdN6ANoCEdAlTxtorWiDnV9lChoBkdAYZ5Ek0JnhGgHTegDaAhHQJVQrYoRZlp1fZQoaAZHQGQf19ORDCxoB03oA2gIR0CVUPWfK6nSdX2UKGgGR0BjsmpXIU8FaAdN6ANoCEdAlVJI1He7+XV9lChoBkdAYoswhW5pamgHTegDaAhHQJVSX0XgtOF1fZQoaAZHQHJ80KRdQfpoB015A2gIR0CVUmsoUi6hdX2UKGgGR0Bi8xDgIhQnaAdN6ANoCEdAlVKxgy/KyXV9lChoBkdAZrnaX8fmtGgHTegDaAhHQJVTi0mdAgR1fZQoaAZHQGK+00vXbudoB03oA2gIR0CVVnkUbkwOdX2UKGgGR0BjAQhB7eEaaAdN6ANoCEdAlVmnyAhB7nV9lChoBkdASGUf5k9U0mgHTQUBaAhHQJVc7ChvitJ1fZQoaAZHQGQRcWj4595oB03oA2gIR0CVYfgUlAu7dX2UKGgGR0BhCW3H7xd6aAdN6ANoCEdAlWKIDxLCenV9lChoBkdAYu39Wp6yB2gHTegDaAhHQJVmgK1G9Yh1fZQoaAZHQGeL9LpRoAZoB03oA2gIR0CVg/VrylN2dX2UKGgGR0BgNat7rs0IaAdN6ANoCEdAlYlIRh+fAnV9lChoBkdAZVmTq0MPSWgHTegDaAhHQJWJSWTot+V1fZQoaAZHQHHJVZX+2mZoB01/A2gIR0CViWj9GZuydX2UKGgGR0BbQVWS2Yv4aAdN6ANoCEdAlYrWPT5O8HV9lChoBkdAYHti++M6zWgHTegDaAhHQJWLOyyD7Il1fZQoaAZHQGDZy/KyOaRoB03oA2gIR0CVi4O4G2TgdWUu"}, "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": "2.5.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "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 0x7a00a7008a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a00a7008af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a00a7008b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a00a7008c10>", "_build": "<function ActorCriticPolicy._build at 0x7a00a7008ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7a00a7008d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a00a7008dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a00a7008e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7a00a7008ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a00a7008f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a00a7009000>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a00a7009090>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a0049ec2a40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1731876445950991976, "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": -0.007616000000000067, "_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": 992, "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, "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:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "2.5.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v3.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:73ad1057b11ef021e6e2149fe6ebf85db6aa5fe9152554a78a1988f00aca9cd3
|
| 3 |
+
size 148064
|
ppo-LunarLander-v3/_stable_baselines3_version
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
2.0.0a5
|
ppo-LunarLander-v3/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 0x7a00a7008a60>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a00a7008af0>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a00a7008b80>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a00a7008c10>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7a00a7008ca0>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7a00a7008d30>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7a00a7008dc0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a00a7008e50>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7a00a7008ee0>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a00a7008f70>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a00a7009000>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7a00a7009090>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7a0049ec2a40>"
|
| 21 |
+
},
|
| 22 |
+
"verbose": 1,
|
| 23 |
+
"policy_kwargs": {},
|
| 24 |
+
"num_timesteps": 2015232,
|
| 25 |
+
"_total_timesteps": 2000000,
|
| 26 |
+
"_num_timesteps_at_start": 0,
|
| 27 |
+
"seed": null,
|
| 28 |
+
"action_noise": null,
|
| 29 |
+
"start_time": 1731876445950991976,
|
| 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": -0.007616000000000067,
|
| 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": 992,
|
| 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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
| 73 |
+
"n": "4",
|
| 74 |
+
"start": "0",
|
| 75 |
+
"_shape": [],
|
| 76 |
+
"dtype": "int64",
|
| 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 |
+
}
|
ppo-LunarLander-v3/policy.optimizer.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f66fe399450ae064bdafd0882bd159c3da0f6363485aff2e796ee4678896d8ed
|
| 3 |
+
size 88490
|
ppo-LunarLander-v3/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:10736d5859d0405b535afe9c6e0cfdac727bf1a17db677ec71e52798a9c58378
|
| 3 |
+
size 43762
|
ppo-LunarLander-v3/pytorch_variables.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
| 3 |
+
size 864
|
ppo-LunarLander-v3/system_info.txt
ADDED
|
@@ -0,0 +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: 2.5.1+cu121
|
| 5 |
+
- GPU Enabled: True
|
| 6 |
+
- Numpy: 1.26.4
|
| 7 |
+
- Cloudpickle: 3.1.0
|
| 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": 294.9566451, "std_reward": 15.679243213879348, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-11-17T21:11:34.462649"}
|