Initial checkpoint

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,28 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 281.88 +/- 14.38
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+  # **PPO** Agent playing **LunarLander-v2**
+  This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+  
+  ## Usage (with Stable-baselines3)
+  TODO: Add your code
+  

config.json

@@ -0,0 +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 0x7f72bdfce290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f72bdfce320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f72bdfce3b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f72bdfce440>", "_build": "<function ActorCriticPolicy._build at 0x7f72bdfce4d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f72bdfce560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f72bdfce5f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f72bdfce680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f72bdfce710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f72bdfce7a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f72bdfce830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f72be010d80>"}, "verbose": 1, "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": 16, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651674967.636708, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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": 620, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo0.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:425a7efe8d1c8f4e153890634e260aadbcd77a8fd4884d5cf6774104777da4c2
+size 143984

ppo0/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

ppo0/data

@@ -0,0 +1,94 @@
+{
+    "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 0x7f72bdfce290>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f72bdfce320>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f72bdfce3b0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f72bdfce440>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f72bdfce4d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f72bdfce560>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f72bdfce5f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f72bdfce680>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f72bdfce710>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f72bdfce7a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f72bdfce830>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f72be010d80>"
+    },
+    "verbose": 1,
+    "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": 16,
+    "num_timesteps": 2031616,
+    "_total_timesteps": 2000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1651674967.636708,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_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:": "gAWVIRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI9DEfEGibcECUhpRSlIwBbJRLq4wBdJRHQLIRf3ZPEbZ1fZQoaAZoCWgPQwhselBQSqFzQJSGlFKUaBVLwWgWR0CyEYk8RtgsdX2UKGgGaAloD0MI+HDJcafycUCUhpRSlGgVS8BoFkdAshGTBacI7nV9lChoBmgJaA9DCF6fOevT7nNAlIaUUpRoFUu3aBZHQLIRnwBYFJR1fZQoaAZoCWgPQwhXem021ptyQJSGlFKUaBVL0GgWR0CyEaNeQdS3dX2UKGgGaAloD0MIrkm3JbK2cUCUhpRSlGgVS8loFkdAshHLOu7pV3V9lChoBmgJaA9DCOeKUkIwiXFAlIaUUpRoFUvCaBZHQLIR01He7+V1fZQoaAZoCWgPQwjdCfZf51hxQJSGlFKUaBVLuWgWR0CyEdXCoCMhdX2UKGgGaAloD0MIAb7bvPEcckCUhpRSlGgVS8NoFkdAshJYR15jY3V9lChoBmgJaA9DCBqk4ClkBnFAlIaUUpRoFUu5aBZHQLISWtdRiw11fZQoaAZoCWgPQwio5JzYA4FyQJSGlFKUaBVNCAFoFkdAshKYfHPu5XV9lChoBmgJaA9DCGQke4Ra+3FAlIaUUpRoFUuuaBZHQLISqBPsRg91fZQoaAZoCWgPQwhJ1XYTvOJyQJSGlFKUaBVLzWgWR0CyErh19v0idX2UKGgGaAloD0MINXugFZipcUCUhpRSlGgVS7FoFkdAshLcKQaJh3V9lChoBmgJaA9DCBTRr61fy3JAlIaUUpRoFUu6aBZHQLIS+KfWcz91fZQoaAZoCWgPQwirWtJRjldwQJSGlFKUaBVLrmgWR0CyEvi5y2hJdX2UKGgGaAloD0MIhIO9iaFGcECUhpRSlGgVS5toFkdAshMP93r2QHV9lChoBmgJaA9DCLyQDg9hN3JAlIaUUpRoFUvHaBZHQLITHg/Tspp1fZQoaAZoCWgPQwgCm3PwjJJwQJSGlFKUaBVLqWgWR0CyEylz6rNodX2UKGgGaAloD0MIaR7AIv+hcUCUhpRSlGgVS8FoFkdAshNQyi22HHV9lChoBmgJaA9DCEoKLIDpmnFAlIaUUpRoFUvcaBZHQLITWoWHk951fZQoaAZoCWgPQwiqJ/OPftlxQJSGlFKUaBVLmWgWR0CyE+bor4FidX2UKGgGaAloD0MIdM5PcRxlc0CUhpRSlGgVS6FoFkdAshQLP7el9HV9lChoBmgJaA9DCPg0Jy9yiHFAlIaUUpRoFUvVaBZHQLIUIFINEw51fZQoaAZoCWgPQwj9hokGKWpxQJSGlFKUaBVLumgWR0CyFCP8dgfEdX2UKGgGaAloD0MIdAmH3uIsUECUhpRSlGgVS2JoFkdAshQ3MibDuXV9lChoBmgJaA9DCMf2WtA7BXJAlIaUUpRoFUuiaBZHQLIUOyRB/qh1fZQoaAZoCWgPQwj9ZmK6UKNzQJSGlFKUaBVL52gWR0CyFEdz4k/sdX2UKGgGaAloD0MIO1W+Z+TDckCUhpRSlGgVS55oFkdAshRP6eoUBXV9lChoBmgJaA9DCJXXSuiuPHNAlIaUUpRoFUu9aBZHQLIUi6uGKyh1fZQoaAZoCWgPQwgm/b0UnrlwQJSGlFKUaBVLsmgWR0CyFJv5k9U0dX2UKGgGaAloD0MIIk+SrpkQckCUhpRSlGgVS5loFkdAshScDlo11nV9lChoBmgJaA9DCGR47GexzXBAlIaUUpRoFUuvaBZHQLIUoRlHz6J1fZQoaAZoCWgPQwgogc05OI5wQJSGlFKUaBVLwWgWR0CyFKzVx0dSdX2UKGgGaAloD0MI2QbuQB3hcUCUhpRSlGgVS6hoFkdAshWSAskIHHV9lChoBmgJaA9DCE8Hsp6arnFAlIaUUpRoFUvGaBZHQLIVojy4FzN1fZQoaAZoCWgPQwiwHvet1vVwQJSGlFKUaBVLmmgWR0CyFaT+irT6dX2UKGgGaAloD0MITz49tmVHckCUhpRSlGgVS6ZoFkdAshWpzo2XLXV9lChoBmgJaA9DCNXMWgpIzm9AlIaUUpRoFUu6aBZHQLIVrFVDKHR1fZQoaAZoCWgPQwhKCcGqephyQJSGlFKUaBVLxmgWR0CyFdrLt/nXdX2UKGgGaAloD0MIUYU/w5uncUCUhpRSlGgVS8VoFkdAshX5cD8tPHV9lChoBmgJaA9DCBk3NdA8SXJAlIaUUpRoFUvUaBZHQLIWCN70Fr51fZQoaAZoCWgPQwiCyvj3WWdwQJSGlFKUaBVLomgWR0CyFhtxQzk7dX2UKGgGaAloD0MIkunQ6bm1cECUhpRSlGgVS7NoFkdAshYugyuZC3V9lChoBmgJaA9DCGyvBb13CHNAlIaUUpRoFUu4aBZHQLIWOtnwob51fZQoaAZoCWgPQwgMVpxqLcBxQJSGlFKUaBVLw2gWR0CyFkIhY/3WdX2UKGgGaAloD0MIkbjH0ofdcECUhpRSlGgVS7xoFkdAshZISWZ7X3V9lChoBmgJaA9DCMkBu5p8vnFAlIaUUpRoFUuTaBZHQLIW0yJ9Aop1fZQoaAZoCWgPQwiRe7q6o0NxQJSGlFKUaBVLjmgWR0CyFt+Il+mWdX2UKGgGaAloD0MIV3cstkmBckCUhpRSlGgVS61oFkdAshcm9i+cpnV9lChoBmgJaA9DCGxc/64PD3FAlIaUUpRoFUu7aBZHQLIXQ3rleWx1fZQoaAZoCWgPQwjfMqfLIj9xQJSGlFKUaBVLk2gWR0CyF1P6TGHYdX2UKGgGaAloD0MIuqC+Zc50YkCUhpRSlGgVTegDaBZHQLIXhOgQHzJ1fZQoaAZoCWgPQwiu8gTCjuNyQJSGlFKUaBVL12gWR0CyF4UjkdWAdX2UKGgGaAloD0MIndoZpjaXckCUhpRSlGgVS6FoFkdAsheaOdXkpHV9lChoBmgJaA9DCN52obkOkXFAlIaUUpRoFUu+aBZHQLIXwzbN8md1fZQoaAZoCWgPQwjo9pLG6A90QJSGlFKUaBVLtmgWR0CyF9CP+4smdX2UKGgGaAloD0MIfqg0YuaBckCUhpRSlGgVS91oFkdAshfjCDVYp3V9lChoBmgJaA9DCALTad3Gv3FAlIaUUpRoFUu+aBZHQLIX54ubqhV1fZQoaAZoCWgPQwhpVrYP+TxkQJSGlFKUaBVN6ANoFkdAshfo+KTB7HV9lChoBmgJaA9DCJXVdD2RuHNAlIaUUpRoFUvuaBZHQLIX6T987ZF1fZQoaAZoCWgPQwjNAu0O6XJxQJSGlFKUaBVLz2gWR0CyGAck2P1ddX2UKGgGaAloD0MIaHqJsYwEckCUhpRSlGgVS6NoFkdAshgq0TlDGHV9lChoBmgJaA9DCLBW7ZpQtHBAlIaUUpRoFUucaBZHQLIYgbsWweN1fZQoaAZoCWgPQwie0yzQbtBvQJSGlFKUaBVLtGgWR0CyGI3bRF7VdX2UKGgGaAloD0MIkdYYdEJXcUCUhpRSlGgVS9poFkdAshidtfoicHV9lChoBmgJaA9DCGgFhqzuw3JAlIaUUpRoFUvMaBZHQLIY00AtFrl1fZQoaAZoCWgPQwgV/gxvFs1xQJSGlFKUaBVLvmgWR0CyGO+6qbSadX2UKGgGaAloD0MIIVwBhTpOcUCUhpRSlGgVS6RoFkdAshkBwNsnA3V9lChoBmgJaA9DCO+qB8yDGnJAlIaUUpRoFUvDaBZHQLIZDMlkYoB1fZQoaAZoCWgPQwiSQINNnbdvQJSGlFKUaBVLo2gWR0CyGRhib2DhdX2UKGgGaAloD0MIXiwMkdPGbUCUhpRSlGgVS6ZoFkdAshkaJyhi9nV9lChoBmgJaA9DCF1sWikEV3FAlIaUUpRoFUu7aBZHQLIZJSCe2/l1fZQoaAZoCWgPQwi9HHbfsfVxQJSGlFKUaBVL42gWR0CyGTlSCOFQdX2UKGgGaAloD0MIIXU7+8qEZECUhpRSlGgVTegDaBZHQLIZUtGd7OV1fZQoaAZoCWgPQwjvyFhtfktxQJSGlFKUaBVL3GgWR0CyGYUwztTldX2UKGgGaAloD0MIkrJF0m55ckCUhpRSlGgVS81oFkdAshmM+gUUPHV9lChoBmgJaA9DCCJRaFk3CnJAlIaUUpRoFUvAaBZHQLIZmuzQeFN1fZQoaAZoCWgPQwie0yzQ7otzQJSGlFKUaBVL82gWR0CyGastCiRGdX2UKGgGaAloD0MIl3K+2Ptpb0CUhpRSlGgVS6xoFkdAshnE/t6X0HV9lChoBmgJaA9DCM6njlVK8UVAlIaUUpRoFUtiaBZHQLIZyAQxveh1fZQoaAZoCWgPQwhqErwhDWtyQJSGlFKUaBVLsGgWR0CyGdRlMAWBdX2UKGgGaAloD0MIDhKifMHUc0CUhpRSlGgVS7NoFkdAshoSqyWzGHV9lChoBmgJaA9DCDcAGxDhrXFAlIaUUpRoFUugaBZHQLIaG8twrDt1fZQoaAZoCWgPQwiUha+vNZJyQJSGlFKUaBVL22gWR0CyGiidFvycdX2UKGgGaAloD0MI2LYos4GyckCUhpRSlGgVS7VoFkdAshovzYmLL3V9lChoBmgJaA9DCBgIAmToa25AlIaUUpRoFUugaBZHQLIaL7HAAQx1fZQoaAZoCWgPQwjQ0hVsY9RwQJSGlFKUaBVLr2gWR0CyGlPcnE2pdX2UKGgGaAloD0MIxM2pZMCnc0CUhpRSlGgVS9RoFkdAshp9ezD4xnV9lChoBmgJaA9DCHh8e9dgwnJAlIaUUpRoFUvBaBZHQLIamRR/EwZ1fZQoaAZoCWgPQwgydy0hH+ZxQJSGlFKUaBVL0GgWR0CyGp1rl/6PdX2UKGgGaAloD0MINPRPcHGQcECUhpRSlGgVS55oFkdAshqiLxZuAXV9lChoBmgJaA9DCDeq04EsT29AlIaUUpRoFUupaBZHQLIaprDZUUB1fZQoaAZoCWgPQwgWGLK6FRpwQJSGlFKUaBVLsWgWR0CyGqwosqaxdX2UKGgGaAloD0MITI3Qz5QEcUCUhpRSlGgVS6FoFkdAshq1+z+m33V9lChoBmgJaA9DCFMI5BIHNnJAlIaUUpRoFUuaaBZHQLIaw4Vh1DB1fZQoaAZoCWgPQwhmTwKbs/1wQJSGlFKUaBVLo2gWR0CyGt9Mbm2cdX2UKGgGaAloD0MIqU9yh03Yb0CUhpRSlGgVS5toFkdAshsNyWAwwnV9lChoBmgJaA9DCBb59UPso3BAlIaUUpRoFUvNaBZHQLIbFdbgTAZ1fZQoaAZoCWgPQwghVn+E4ZNuQJSGlFKUaBVLnmgWR0CyGx0Wl/H6dWUu"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 620,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo0/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8b35ad7aaafc815a066cb47074214c2f675fb9e2e30c46fec229cf8c250f9549
+size 84893

ppo0/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:53fc25dc306edfb27de109c70f01d379a426ede59cb722c73a55c8f847d045b9
+size 43201

ppo0/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo0/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1413742978abdd993833f62eeb0f1baead993fb3c489e433c486defc89610770
+size 211682

results.json

@@ -0,0 +1 @@
+{"mean_reward": 281.8846116039048, "std_reward": 14.377386351276584, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T16:41:42.393379"}