First model for ppo-LunarLander-v2

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 246.18 +/- 17.99
+      name: mean_reward
+      verified: false
+---
+
+# **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
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

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 0x7ff6aa321ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff6aa321d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff6aa321dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff6aa321e50>", "_build": "<function ActorCriticPolicy._build at 0x7ff6aa321ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7ff6aa321f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff6aa326040>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff6aa3260d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff6aa326160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff6aa3261f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff6aa326280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff6aa3204e0>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1672681627999434344, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADMNlT17ApW6ffV/u2GbtjjRUb46Ur4IOgAAgD8AAIA/mnM/PFxTZ7qe7cK7szXoN05LlDsiKgy3AACAPwAAgD/DusG+jeOuPtZliT7hE4y+p3CSvTKhNj4AAAAAAAAAAM34ob00/Lg/f7O4vjG2Rr5fkQa+/dglvgAAAAAAAAAAmmzAvFzTaLp6k9g6plQFtdBwULsNwvm5AACAPwAAgD+aEOg8MPHKPsjWwb09D6i+WDQNvdKrv70AAAAAAAAAAFoclT0p5Fy6pgbSu13hMzj3O/q6Rg57twAAgD8AAIA/ADH1vK4ZrLo6rg070C9HN6RRorkDDNg1AACAPwAAgD8AMYa8H52EudokRrveFWq1HnaDOZ3bZzoAAIA/AACAP4A7Sr6rHI8+Zo0yPnMxDL7nZzY+MtBBuwAAAAAAAAAAZvZdPYvP6z2IgHy97bf+vRjGlD3z09S9AAAAAAAAAABz0xE+3KMAvHXM8Lo5ta041yVXvQiSHToAAIA/AACAP4051b3hDIq6XjyttwKI/bKW9dA6XXXHNgAAgD8AAIA/ZsdAvbiO1bkSg1e6AHX7tfBpgruKUW01AACAPwAAgD8zSWA8lOzOPQVimrzQQtK9uH6BPdDcLDwAAAAAAAAAAFrqxD2bghg/ovtuPVnCZb5v+aA91mw0vAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "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-first-model.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63b337d30c5901c79c1d122dc8b832ef4a5bbf0dc86a4eccefbb3de2cfb97ee4
+size 147210

ppo-LunarLander-first-model/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

ppo-LunarLander-first-model/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 0x7ff6aa321ca0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff6aa321d30>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff6aa321dc0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff6aa321e50>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff6aa321ee0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff6aa321f70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff6aa326040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff6aa3260d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff6aa326160>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff6aa3261f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff6aa326280>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ff6aa3204e0>"
+    },
+    "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": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1672681627999434344,
+    "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:": "gAWVexAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIwOldvB8uXECUhpRSlIwBbJRN6AOMAXSUR0CV3otbs4T9dX2UKGgGaAloD0MI18IstHPqZECUhpRSlGgVTegDaBZHQJXfkQe3hGZ1fZQoaAZoCWgPQwiCxkyiXnRiQJSGlFKUaBVN6ANoFkdAleZV3MY/FHV9lChoBmgJaA9DCMVW0LRECWVAlIaUUpRoFU3oA2gWR0CV619RrJr+dX2UKGgGaAloD0MIz/dT4yVZYkCUhpRSlGgVTegDaBZHQJXwVtuUD+11fZQoaAZoCWgPQwg9gEV+faNiQJSGlFKUaBVN6ANoFkdAlfJaBRQ793V9lChoBmgJaA9DCDOkiuJVFGRAlIaUUpRoFU3oA2gWR0CV9iYzBRAKdX2UKGgGaAloD0MIbhlwlhJ4Y0CUhpRSlGgVTegDaBZHQJX6Zt1p0wJ1fZQoaAZoCWgPQwgsgZTYtR5jQJSGlFKUaBVN6ANoFkdAlg5uZ1FH8XV9lChoBmgJaA9DCNwuNNfp+mZAlIaUUpRoFU3oA2gWR0CWE/o0Q9RrdX2UKGgGaAloD0MIW3wKgPG/XkCUhpRSlGgVTegDaBZHQJYcDLFGXol1fZQoaAZoCWgPQwjrAfOQKb5fQJSGlFKUaBVN6ANoFkdAlhwqqwQlKXV9lChoBmgJaA9DCDPcgM+P+2BAlIaUUpRoFU3oA2gWR0CWHwnnMdLhdX2UKGgGaAloD0MI7+apDjnxYkCUhpRSlGgVTegDaBZHQJYo4kfLcKx1fZQoaAZoCWgPQwh80/TZgWVhQJSGlFKUaBVN6ANoFkdAlipjkdV/+nV9lChoBmgJaA9DCFn4+loXEWNAlIaUUpRoFU3oA2gWR0CWKmb0voNedX2UKGgGaAloD0MIpABRMGO6YkCUhpRSlGgVTegDaBZHQJYrpMewLVp1fZQoaAZoCWgPQwi2oPfGEK5aQJSGlFKUaBVN6ANoFkdAliyshLXcxnV9lChoBmgJaA9DCHMqGQAqzGxAlIaUUpRoFU0wAWgWR0CWMDs1baAXdX2UKGgGaAloD0MI48eYuxZJYkCUhpRSlGgVTegDaBZHQJYzFBzFMqV1fZQoaAZoCWgPQwgAxF29ihplQJSGlFKUaBVN6ANoFkdAljedBKL88HV9lChoBmgJaA9DCN/6sN6oGGNAlIaUUpRoFU3oA2gWR0CWPDdHlOoHdX2UKGgGaAloD0MI3Xh3ZCy1ZECUhpRSlGgVTegDaBZHQJY+FBAv+Ox1fZQoaAZoCWgPQwjAywwb5aBiQJSGlFKUaBVN6ANoFkdAlkHuuA7Pp3V9lChoBmgJaA9DCA5lqIqpYWJAlIaUUpRoFU3oA2gWR0CWRkQ+2VmjdX2UKGgGaAloD0MIrWwf8pbkYkCUhpRSlGgVTegDaBZHQJZG2lLvkR11fZQoaAZoCWgPQwgfuwuUlOVgQJSGlFKUaBVN6ANoFkdAlmAO5z5oG3V9lChoBmgJaA9DCCxhbYwdN2JAlIaUUpRoFU3oA2gWR0CWaQzUZvUCdX2UKGgGaAloD0MIChFwCFVrZECUhpRSlGgVTegDaBZHQJZpLnnuAqd1fZQoaAZoCWgPQwgCK4cW2WNsQJSGlFKUaBVNqQNoFkdAlneVdTo+wHV9lChoBmgJaA9DCPYksDkHUmBAlIaUUpRoFU3oA2gWR0CWeLMUypJgdX2UKGgGaAloD0MIEynN5vHiYkCUhpRSlGgVTegDaBZHQJZ6ahJyyUt1fZQoaAZoCWgPQwiGVidnqP9iQJSGlFKUaBVN6ANoFkdAlnptDYywfXV9lChoBmgJaA9DCGcKnddYTmJAlIaUUpRoFU3oA2gWR0CWfTradtl7dX2UKGgGaAloD0MI5DEDlfFOY0CUhpRSlGgVTegDaBZHQJaBuODJ2dN1fZQoaAZoCWgPQwjVr3Q+PHsrQJSGlFKUaBVLpWgWR0CWgzvHtF8YdX2UKGgGaAloD0MIkfEolfBlZUCUhpRSlGgVTegDaBZHQJaFGy2QXAN1fZQoaAZoCWgPQwhkd4GSgn9iQJSGlFKUaBVN6ANoFkdAloo+pGWldnV9lChoBmgJaA9DCGtHcY66J3BAlIaUUpRoFU0YAWgWR0CWi3fEXLvDdX2UKGgGaAloD0MIyGEwfwXGYUCUhpRSlGgVTegDaBZHQJaPeUxEfDF1fZQoaAZoCWgPQwjQY5Rn3u1gQJSGlFKUaBVN6ANoFkdAlpGfN7jT8nV9lChoBmgJaA9DCOcXJeiv0GJAlIaUUpRoFU3oA2gWR0CWlYPY4ACGdX2UKGgGaAloD0MIz2irksh/XkCUhpRSlGgVTegDaBZHQJaZ4pWmxdJ1fZQoaAZoCWgPQwg+JefEHoJBQJSGlFKUaBVLsWgWR0CWmlw5NoJzdX2UKGgGaAloD0MIfHvXoC86YkCUhpRSlGgVTegDaBZHQJaaenP3SKF1fZQoaAZoCWgPQwhxOPOrOZNcQJSGlFKUaBVN6ANoFkdAlrO1/H5rQHV9lChoBmgJaA9DCPT8aaM6SGNAlIaUUpRoFU3oA2gWR0CWu/D1XeWOdX2UKGgGaAloD0MIbw1sleAPZECUhpRSlGgVTegDaBZHQJa8EJTl1bJ1fZQoaAZoCWgPQwjhKeRKvdphQJSGlFKUaBVN6ANoFkdAlsmZRoAXEnV9lChoBmgJaA9DCJSHhVrThWFAlIaUUpRoFU3oA2gWR0CWzHODaoMsdX2UKGgGaAloD0MI04bD0sBpY0CUhpRSlGgVTegDaBZHQJbPcurZJ051fZQoaAZoCWgPQwgXR+Um6v5hQJSGlFKUaBVN6ANoFkdAltR8e8wpOXV9lChoBmgJaA9DCGlTdY9s+2FAlIaUUpRoFU3oA2gWR0CW1i/iYLLIdX2UKGgGaAloD0MIwf2AB4ZwY0CUhpRSlGgVTegDaBZHQJbYKQEIPbx1fZQoaAZoCWgPQwhUVtP1RPVhQJSGlFKUaBVN6ANoFkdAlt3KS5iEx3V9lChoBmgJaA9DCO8dNSbEQmVAlIaUUpRoFU3oA2gWR0CW3yCcf/3ndX2UKGgGaAloD0MIHF2lu+tHYUCUhpRSlGgVTegDaBZHQJbleIEbHZN1fZQoaAZoCWgPQwi/79+8OCEYQJSGlFKUaBVNaQFoFkdAlucig9Net3V9lChoBmgJaA9DCGzQl97+QGNAlIaUUpRoFU3oA2gWR0CW6V3zcynDdX2UKGgGaAloD0MIttjts8r+YUCUhpRSlGgVTegDaBZHQJbt4/FBIFx1fZQoaAZoCWgPQwgNbQA2oFljQJSGlFKUaBVN6ANoFkdAlu5m4iHIqHV9lChoBmgJaA9DCPKwUGua12JAlIaUUpRoFU3oA2gWR0CW7oOqebuudX2UKGgGaAloD0MIsg+yLJhdYUCUhpRSlGgVTegDaBZHQJcHrRplBhR1fZQoaAZoCWgPQwjon+BiRQdhQJSGlFKUaBVN6ANoFkdAlxA2z0HyE3V9lChoBmgJaA9DCIJV9fI7NGBAlIaUUpRoFU3oA2gWR0CXEFnyup0fdX2UKGgGaAloD0MICvX0Efh7IECUhpRSlGgVTS4BaBZHQJcUJdIGyHF1fZQoaAZoCWgPQwgOTkS/tnVlQJSGlFKUaBVN6ANoFkdAlxyuI68xsXV9lChoBmgJaA9DCASOBBrsw2BAlIaUUpRoFU3oA2gWR0CXHxPNVzZIdX2UKGgGaAloD0MINqypLArfQkCUhpRSlGgVS9BoFkdAlyDlwDNhVnV9lChoBmgJaA9DCHDSNCiaJWJAlIaUUpRoFU3oA2gWR0CXJdsunMt9dX2UKGgGaAloD0MIvY44ZAOqYUCUhpRSlGgVTegDaBZHQJcnPjQzDXR1fZQoaAZoCWgPQwjhRsoWySJjQJSGlFKUaBVN6ANoFkdAlykNNvfj0nV9lChoBmgJaA9DCBAIdCZtKEVAlIaUUpRoFUvVaBZHQJcrcRcu8K51fZQoaAZoCWgPQwizCMVWUHxhQJSGlFKUaBVN6ANoFkdAly32g8KXwHV9lChoBmgJaA9DCElm9Q63UWFAlIaUUpRoFU3oA2gWR0CXLyVYZEUkdX2UKGgGaAloD0MIyqgyjLvmY0CUhpRSlGgVTegDaBZHQJc0LCm/Fit1fZQoaAZoCWgPQwjbw14o4FRgQJSGlFKUaBVN6ANoFkdAlzWcefZmI3V9lChoBmgJaA9DCAu3fCSlv2FAlIaUUpRoFU3oA2gWR0CXN59l2/zrdX2UKGgGaAloD0MIrFj8prBKP0CUhpRSlGgVTUUBaBZHQJc48g3cYZV1fZQoaAZoCWgPQwjf+Nozy1VmQJSGlFKUaBVN6ANoFkdAlzu2LDQ7cXV9lChoBmgJaA9DCHQjLCpivmNAlIaUUpRoFU3oA2gWR0CXPITgl4TsdX2UKGgGaAloD0MIWikEcolyYkCUhpRSlGgVTegDaBZHQJdaty4nWrh1fZQoaAZoCWgPQwhZ3eo5aeRjQJSGlFKUaBVN6ANoFkdAl2K9cnmaIHV9lChoBmgJaA9DCA2NJ4I4zWFAlIaUUpRoFU3oA2gWR0CXYt3Zwn6VdX2UKGgGaAloD0MIMjuL3qmUY0CUhpRSlGgVTegDaBZHQJdvZj2Bas91fZQoaAZoCWgPQwh/hcyVQVVWQJSGlFKUaBVN6ANoFkdAl3QUHdGiH3V9lChoBmgJaA9DCJ7r+3AQFWJAlIaUUpRoFU3oA2gWR0CXeXyWRigCdX2UKGgGaAloD0MIxY1bzE9JZECUhpRSlGgVTegDaBZHQJd89U4rBj51fZQoaAZoCWgPQwhj7lpCPqJkQJSGlFKUaBVN6ANoFkdAl39/oaDPGHV9lChoBmgJaA9DCL+1EyUhBGBAlIaUUpRoFU3oA2gWR0CXgiz67/XHdX2UKGgGaAloD0MI4Xmp2BjQY0CUhpRSlGgVTegDaBZHQJeDVWEK3NN1fZQoaAZoCWgPQwiQos7cQ2hMQJSGlFKUaBVLvmgWR0CXh8rK/20zdX2UKGgGaAloD0MIJefEHlrKZECUhpRSlGgVTegDaBZHQJeI5psXSBt1fZQoaAZoCWgPQwjK4ZNOJD9jQJSGlFKUaBVN6ANoFkdAl4pRB3RoiHV9lChoBmgJaA9DCDfHuU24D2ZAlIaUUpRoFU3oA2gWR0CXjIl7+kxidX2UKGgGaAloD0MIsvFgi93gXkCUhpRSlGgVTegDaBZHQJeNtwl0HQh1fZQoaAZoCWgPQwgTY5l+idRgQJSGlFKUaBVN6ANoFkdAl5AR9G7SRnV9lChoBmgJaA9DCJzhBnz+dWVAlIaUUpRoFU3oA2gWR0CXkI1dPci4dX2UKGgGaAloD0MICtrk8EmXQ0CUhpRSlGgVS6VoFkdAl5F9FKCg9XV9lChoBmgJaA9DCDFfXoB9a2RAlIaUUpRoFU3oA2gWR0CXlXhkAggYdWUu"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
+    "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
+}

ppo-LunarLander-first-model/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1ae3d17eb871bf5b46a239bdaa2482749bb22741e6f90ca44834c765e776a489
+size 87929

ppo-LunarLander-first-model/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee026cc3b9a1ac37a0144f7b662d2d72cc28efc7724e42516eb9d08f265283cd
+size 43201

ppo-LunarLander-first-model/pytorch_variables.pth

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

ppo-LunarLander-first-model/system_info.txt

@@ -0,0 +1,7 @@
+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

results.json

@@ -0,0 +1 @@
+{"mean_reward": 246.17510452025527, "std_reward": 17.992064238238736, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-02T18:13:05.252269"}