dficenec commited on
Commit
7c60cb2
1 Parent(s): 56194ae

Initial training run

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 285.31 +/- 28.68
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 280.15 +/- 21.59
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f2051d1cd30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2051d1cdc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2051d1ce50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2051d1cee0>", "_build": "<function ActorCriticPolicy._build at 0x7f2051d1cf70>", "forward": "<function ActorCriticPolicy.forward at 0x7f2051d22040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2051d220d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2051d22160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2051d221f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2051d22280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2051d22310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2051d1d210>"}, "verbose": 0, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 8, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670786404348067830, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVgBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIz6Chf4LzZ0CUhpRSlIwBbJRN6AOMAXSUR0CbcMqynk1edX2UKGgGaAloD0MIV1uxv+yHY0CUhpRSlGgVTegDaBZHQJu/DwPRRdh1fZQoaAZoCWgPQwgvFLAdDANiQJSGlFKUaBVN6ANoFkdAm7/9xyXD33V9lChoBmgJaA9DCFyq0hZXcmJAlIaUUpRoFU3oA2gWR0CbxL4n4O+adX2UKGgGaAloD0MIFCUhkba8ZUCUhpRSlGgVTegDaBZHQJvFq2iL2pR1fZQoaAZoCWgPQwhz8bc9QTFlQJSGlFKUaBVN6ANoFkdAm8Yc6V+qi3V9lChoBmgJaA9DCEjA6PJmc2NAlIaUUpRoFU3oA2gWR0CbzvY3Ns3ydX2UKGgGaAloD0MIv5tu2aEjY0CUhpRSlGgVTegDaBZHQJvPHr/sE7p1fZQoaAZoCWgPQwhblUT2QUZlQJSGlFKUaBVN6ANoFkdAm9NbB9Cu2nV9lChoBmgJaA9DCO+RzVXzw2JAlIaUUpRoFU3oA2gWR0Cb1yzKs+3ZdX2UKGgGaAloD0MIQdMSK6NBY0CUhpRSlGgVTegDaBZHQJvYEp5NXYF1fZQoaAZoCWgPQwhgVijSfetmQJSGlFKUaBVN6ANoFkdAm9zNv863iXV9lChoBmgJaA9DCOKReHk6wWZAlIaUUpRoFU3oA2gWR0Cb3bKQ7tAtdX2UKGgGaAloD0MIQN6rVibJZ0CUhpRSlGgVTegDaBZHQJveG76Hj6x1fZQoaAZoCWgPQwg9EFmkif1wQJSGlFKUaBVNWAFoFkdAm9/Anpjc23V9lChoBmgJaA9DCGRd3EYDyGBAlIaUUpRoFU3oA2gWR0Cb5cjzqbBodX2UKGgGaAloD0MIzAuwj07fZUCUhpRSlGgVTegDaBZHQJvl7n6l+E11fZQoaAZoCWgPQwiSPxh47rNNQJSGlFKUaBVLU2gWR0Cb57TjNpuddX2UKGgGaAloD0MI/fZ14BwQY0CUhpRSlGgVTegDaBZHQJvp6e5Fw1l1fZQoaAZoCWgPQwjd66S+rHhlQJSGlFKUaBVN6ANoFkdAnDtHbh3qzXV9lChoBmgJaA9DCJYkz/V9bmhAlIaUUpRoFU3oA2gWR0CcQMT/hl19dX2UKGgGaAloD0MI529CIYI6ZkCUhpRSlGgVTegDaBZHQJxBqbRWtEJ1fZQoaAZoCWgPQwjB5bFmZOVhQJSGlFKUaBVN6ANoFkdAnEIQaisXBXV9lChoBmgJaA9DCMQJTKd1qWZAlIaUUpRoFU3oA2gWR0CcQ5EYfnwHdX2UKGgGaAloD0MI2JyDZ0LcYkCUhpRSlGgVTegDaBZHQJxJY7tAs051fZQoaAZoCWgPQwjqIK8HE2xmQJSGlFKUaBVN6ANoFkdAnEsxVU+9rXV9lChoBmgJaA9DCJPkub4Pv2ZAlIaUUpRoFU3oA2gWR0CcTW6CUX54dX2UKGgGaAloD0MIZhU2A9x8aECUhpRSlGgVTegDaBZHQJxRRFI/Z/V1fZQoaAZoCWgPQwgAqrhxi15lQJSGlFKUaBVN6ANoFkdAnFeWxdIGyHV9lChoBmgJaA9DCBr4UQ17pmFAlIaUUpRoFU3oA2gWR0CcWHtP557gdX2UKGgGaAloD0MINXwL68aoY0CUhpRSlGgVTegDaBZHQJxY5XeWOZN1fZQoaAZoCWgPQwg2rn/X5+ViQJSGlFKUaBVN6ANoFkdAnFqim65G0HV9lChoBmgJaA9DCECIZMixMmZAlIaUUpRoFU3oA2gWR0CcYU2R7qptdX2UKGgGaAloD0MIx/Za0HvOZ0CUhpRSlGgVTegDaBZHQJxjaYF7laN1fZQoaAZoCWgPQwhp/S0BeNxlQJSGlFKUaBVN6ANoFkdAnGX+BH09Q3V9lChoBmgJaA9DCNDyPLg7zGZAlIaUUpRoFU3oA2gWR0Ccs3ZgogFHdX2UKGgGaAloD0MIr8xbdd0RckCUhpRSlGgVTasDaBZHQJy3wEzO5ax1fZQoaAZoCWgPQwjkwKvljtdwQJSGlFKUaBVNwQNoFkdAnLmmgJ1JUnV9lChoBmgJaA9DCPA1BMflTmNAlIaUUpRoFU3oA2gWR0CcuhnSOR1YdX2UKGgGaAloD0MI7fXuj/ftZkCUhpRSlGgVTegDaBZHQJy8PJEH+qB1fZQoaAZoCWgPQwjL8nUZ/tFlQJSGlFKUaBVN6ANoFkdAnMKd6LOzIHV9lChoBmgJaA9DCGK/J9YpWGRAlIaUUpRoFU3oA2gWR0CcxIr4FiazdX2UKGgGaAloD0MIeNLCZZXIaUCUhpRSlGgVTegDaBZHQJzHDfk3juN1fZQoaAZoCWgPQwgIrYcvkwhqQJSGlFKUaBVN6ANoFkdAnMtEEHMUy3V9lChoBmgJaA9DCG4Xmuu0DmFAlIaUUpRoFU3oA2gWR0Cc0BNhVlwtdX2UKGgGaAloD0MIWybD8XwNZkCUhpRSlGgVTegDaBZHQJzSFQAMlTp1fZQoaAZoCWgPQwiOjxZnjPBhQJSGlFKUaBVN6ANoFkdAnNKNt2s7uHV9lChoBmgJaA9DCAQAx549JGlAlIaUUpRoFU3oA2gWR0Cc1LMrVe8gdX2UKGgGaAloD0MI9Pv+zYsaZkCUhpRSlGgVTegDaBZHQJza89ovi991fZQoaAZoCWgPQwh/hjdrcBZpQJSGlFKUaBVN6ANoFkdAnNzEd/8VHnV9lChoBmgJaA9DCEsfuqA+z2NAlIaUUpRoFU3oA2gWR0Cc3wWD6FdtdX2UKGgGaAloD0MI2GFM+vvVZUCUhpRSlGgVTegDaBZHQJzim85CF9N1fZQoaAZoCWgPQwj/A6xVO4hjQJSGlFKUaBVN6ANoFkdAnTAwZn+Q2nV9lChoBmgJaA9DCIWzW8vkoGdAlIaUUpRoFU3oA2gWR0CdMhC04R29dX2UKGgGaAloD0MIbQN3oM51YUCUhpRSlGgVTegDaBZHQJ0ygQ+UyHp1fZQoaAZoCWgPQwgWo661919oQJSGlFKUaBVN6ANoFkdAnTSRFEy+H3V9lChoBmgJaA9DCPsfYK3a92lAlIaUUpRoFU3oA2gWR0CdOyaF23a0dX2UKGgGaAloD0MIY/Gbwkr9aECUhpRSlGgVTegDaBZHQJ09IpjMFEB1fZQoaAZoCWgPQwhRTUnWYWhlQJSGlFKUaBVN6ANoFkdAnT+RdhRZU3V9lChoBmgJaA9DCCEE5EuopWZAlIaUUpRoFU3oA2gWR0CdQ15Z8rqddX2UKGgGaAloD0MIJGB0eXMJakCUhpRSlGgVTegDaBZHQJ1HvypaRp11fZQoaAZoCWgPQwj/dW7aDO5pQJSGlFKUaBVN6ANoFkdAnUmkpy6tknV9lChoBmgJaA9DCAd40sLlwWJAlIaUUpRoFU3oA2gWR0CdShgF5fMOdX2UKGgGaAloD0MI2Vw1z5G2aECUhpRSlGgVTegDaBZHQJ1ME4Otnwp1fZQoaAZoCWgPQwh+bmjKTrpjQJSGlFKUaBVN6ANoFkdAnVHv0VafSXV9lChoBmgJaA9DCEiI8gUtNWNAlIaUUpRoFU3oA2gWR0CdU6d8Aq/edX2UKGgGaAloD0MI19081aFkc0CUhpRSlGgVTb0DaBZHQJ1UsxM36yl1fZQoaAZoCWgPQwinW3aI/4xoQJSGlFKUaBVN6ANoFkdAnVjOMMqjJ3V9lChoBmgJaA9DCAXFjzF3tWVAlIaUUpRoFU3oA2gWR0CdpaKFZgXudX2UKGgGaAloD0MI74y2KonPY0CUhpRSlGgVTegDaBZHQJ2nNxOtW+51fZQoaAZoCWgPQwiwjXiym1FmQJSGlFKUaBVN6ANoFkdAnaebB42S+3V9lChoBmgJaA9DCGVSQxuATmZAlIaUUpRoFU3oA2gWR0CdqV6Uqx1QdX2UKGgGaAloD0MI5UaRtQbOZUCUhpRSlGgVTegDaBZHQJ2vZPk7wKB1fZQoaAZoCWgPQwiVuflGdA9mQJSGlFKUaBVN6ANoFkdAnbEpuhsZYXV9lChoBmgJaA9DCCU9DK1OiWZAlIaUUpRoFU3oA2gWR0Cdsmx3mmtRdX2UKGgGaAloD0MIgm+aPruwYkCUhpRSlGgVTegDaBZHQJ23GFGoaUB1fZQoaAZoCWgPQwjZQpCDkhdnQJSGlFKUaBVN6ANoFkdAnbvGvfTCtXV9lChoBmgJaA9DCKgAGM+gPmZAlIaUUpRoFU3oA2gWR0CdvZyzXz19dX2UKGgGaAloD0MIBU8hV2qsY0CUhpRSlGgVTegDaBZHQJ2+EJ1JUYN1fZQoaAZoCWgPQwimKQKc3mRjQJSGlFKUaBVN6ANoFkdAncAcRxtHhHV9lChoBmgJaA9DCHMuxVXla2lAlIaUUpRoFU3oA2gWR0CdxlTzundgdX2UKGgGaAloD0MIUkgyq3eGakCUhpRSlGgVTegDaBZHQJ3IENYr8SB1fZQoaAZoCWgPQwj8VBUaCKJkQJSGlFKUaBVN6ANoFkdAnck0CmuTzXV9lChoBmgJaA9DCLjkuFO61GRAlIaUUpRoFU3oA2gWR0CdzSiXpnpTdX2UKGgGaAloD0MI8gcDz72waUCUhpRSlGgVTegDaBZHQJ4af/7zkIZ1fZQoaAZoCWgPQwgUIApmTH5kQJSGlFKUaBVN6ANoFkdAnhwMp1A7gnV9lChoBmgJaA9DCLJoOjuZEWpAlIaUUpRoFU3oA2gWR0CeHG50r9VFdX2UKGgGaAloD0MIotReRFu0akCUhpRSlGgVTegDaBZHQJ4eQSzw+dN1fZQoaAZoCWgPQwiwjXiyGxppQJSGlFKUaBVN6ANoFkdAniRxx95Qg3V9lChoBmgJaA9DCDWbx2GwdWlAlIaUUpRoFU3oA2gWR0CeJkmMwUQDdX2UKGgGaAloD0MIj+TyH5IGc0CUhpRSlGgVTfICaBZHQJ4mq7VawEB1fZQoaAZoCWgPQwhQpzy6EXJqQJSGlFKUaBVN6ANoFkdAnid8r/bTMXV9lChoBmgJaA9DCIdrtYc90mpAlIaUUpRoFU3oA2gWR0CeMT1Fpfx+dX2UKGgGaAloD0MIdO/hkmNIZECUhpRSlGgVTegDaBZHQJ4zWV2Rq491fZQoaAZoCWgPQwhtyD8zCMpkQJSGlFKUaBVN6ANoFkdAnjPS+UQkHHV9lChoBmgJaA9DCMxjzcgg/2JAlIaUUpRoFU3oA2gWR0CeNeeVLSNPdX2UKGgGaAloD0MIEHo2qz71ZkCUhpRSlGgVTegDaBZHQJ48WOAAhjh1fZQoaAZoCWgPQwjqQUEpWvhlQJSGlFKUaBVN6ANoFkdAnj4uUt7KJXV9lChoBmgJaA9DCBNGs7L9iWNAlIaUUpRoFU3oA2gWR0CePo0SRKYidX2UKGgGaAloD0MI+tAF9S3SZkCUhpRSlGgVTegDaBZHQJ4/Vvegte51ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1984, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.015, "vf_coef": 0.5, "max_grad_norm": 0.35, "batch_size": 128, "n_epochs": 32, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
 
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f2051d1cd30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2051d1cdc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2051d1ce50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2051d1cee0>", "_build": "<function ActorCriticPolicy._build at 0x7f2051d1cf70>", "forward": "<function ActorCriticPolicy.forward at 0x7f2051d22040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2051d220d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2051d22160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2051d221f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2051d22280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2051d22310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2051d1d210>"}, "verbose": 0, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 8, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670791282701209686, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1984, "n_steps": 2048, "gamma": 0.9995, "gae_lambda": 0.96, "ent_coef": 0.013, "vf_coef": 0.5, "max_grad_norm": 0.3, "batch_size": 128, "n_epochs": 32, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:2498b156f14019f3ca23d51d4ae01412b0a0a98f26ecc22c8192cd4c6dbf28d0
3
- size 146866
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3a29bcf6ebcdf500668e2582b4fd530bfc9f5fd5cfeccb1eae62f6287fb8490c
3
+ size 146734
ppo-LunarLander-v2/data CHANGED
@@ -47,7 +47,7 @@
47
  "_num_timesteps_at_start": 0,
48
  "seed": null,
49
  "action_noise": null,
50
- "start_time": 1670786404348067830,
51
  "learning_rate": 0.0003,
52
  "tensorboard_log": null,
53
  "lr_schedule": {
@@ -56,7 +56,7 @@
56
  },
57
  "_last_obs": {
58
  ":type:": "<class 'numpy.ndarray'>",
59
- ":serialized:": "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"
60
  },
61
  "_last_episode_starts": {
62
  ":type:": "<class 'numpy.ndarray'>",
@@ -69,7 +69,7 @@
69
  "_current_progress_remaining": -0.015808000000000044,
70
  "ep_info_buffer": {
71
  ":type:": "<class 'collections.deque'>",
72
- ":serialized:": "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"
73
  },
74
  "ep_success_buffer": {
75
  ":type:": "<class 'collections.deque'>",
@@ -77,11 +77,11 @@
77
  },
78
  "_n_updates": 1984,
79
  "n_steps": 2048,
80
- "gamma": 0.999,
81
- "gae_lambda": 0.98,
82
- "ent_coef": 0.015,
83
  "vf_coef": 0.5,
84
- "max_grad_norm": 0.35,
85
  "batch_size": 128,
86
  "n_epochs": 32,
87
  "clip_range": {
 
47
  "_num_timesteps_at_start": 0,
48
  "seed": null,
49
  "action_noise": null,
50
+ "start_time": 1670791282701209686,
51
  "learning_rate": 0.0003,
52
  "tensorboard_log": null,
53
  "lr_schedule": {
 
56
  },
57
  "_last_obs": {
58
  ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
  },
61
  "_last_episode_starts": {
62
  ":type:": "<class 'numpy.ndarray'>",
 
69
  "_current_progress_remaining": -0.015808000000000044,
70
  "ep_info_buffer": {
71
  ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
  },
74
  "ep_success_buffer": {
75
  ":type:": "<class 'collections.deque'>",
 
77
  },
78
  "_n_updates": 1984,
79
  "n_steps": 2048,
80
+ "gamma": 0.9995,
81
+ "gae_lambda": 0.96,
82
+ "ent_coef": 0.013,
83
  "vf_coef": 0.5,
84
+ "max_grad_norm": 0.3,
85
  "batch_size": 128,
86
  "n_epochs": 32,
87
  "clip_range": {
ppo-LunarLander-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:18c8d72a3a76e1a774e5c61b4ae4f108ebb28d68b985f2fab57dec98a9431928
3
  size 87929
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:813b27c0a9dbb5429b3d8fbec6ce6906e4792e1d57de613710c276f447f28cdd
3
  size 87929
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:762ea50dbaf62d13656852a6acdfde550edee4db1eb4aefd1a3e615e6552b1b9
3
  size 43201
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:30883d6c65090b40d457ed598eaad75f2ef0d69c15808fb356d035f47fe00ffd
3
  size 43201
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 285.30866639765424, "std_reward": 28.676550945046486, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T19:56:32.277240"}
 
1
+ {"mean_reward": 280.14667746235875, "std_reward": 21.58929555250594, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T21:11:49.310195"}