Upload PPO LunarLander-v2 trained agent

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: 248.63 +/- 20.70
+      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 0x7fd2c6be7e50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd2c6be7ee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd2c6be7f70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd2c6bec040>", "_build": "<function ActorCriticPolicy._build at 0x7fd2c6bec0d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd2c6bec160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd2c6bec1f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd2c6bec280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd2c6bec310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd2c6bec3a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd2c6bec430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd2c6be5630>"}, "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": 1671979549449488868, "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": 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, "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

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e08d138ac71ed112511e472148430019072a8fbfaa2ee388a5562ebd61e580df
+size 147206

ppo-LunarLander-v2/_stable_baselines3_version

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

ppo-LunarLander-v2/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 0x7fd2c6be7e50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd2c6be7ee0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd2c6be7f70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd2c6bec040>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fd2c6bec0d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fd2c6bec160>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd2c6bec1f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fd2c6bec280>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd2c6bec310>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd2c6bec3a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd2c6bec430>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fd2c6be5630>"
+    },
+    "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": 1671979549449488868,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
+    },
+    "_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:": "gAWVeBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIQG1Up0ODcUCUhpRSlIwBbJRNUAGMAXSUR0CRAKlPrOZ9dX2UKGgGaAloD0MI09ufi4b7cECUhpRSlGgVTVkBaBZHQJEBHtlZowp1fZQoaAZoCWgPQwh/TkF+tgZzQJSGlFKUaBVNLgFoFkdAkQFditq59XV9lChoBmgJaA9DCHcxzXSv8XBAlIaUUpRoFU0tAWgWR0CRAebJwKjSdX2UKGgGaAloD0MIsfz5tuCTbkCUhpRSlGgVTVMBaBZHQJECIVclgMN1fZQoaAZoCWgPQwgSTaCIBcxwQJSGlFKUaBVNQgFoFkdAkQI3uy/sV3V9lChoBmgJaA9DCO/lPjnKb3BAlIaUUpRoFU1eAWgWR0CRA0Sm65G0dX2UKGgGaAloD0MIP/1nzQ89bUCUhpRSlGgVTTEBaBZHQJEESGO+7Dl1fZQoaAZoCWgPQwh5dvnWB09yQJSGlFKUaBVNPQFoFkdAkQRPIXCTEHV9lChoBmgJaA9DCD3uW60T7XBAlIaUUpRoFU0bAWgWR0CRBHR6nivQdX2UKGgGaAloD0MIDhR4J5+9bECUhpRSlGgVTSIBaBZHQJEE18F6iTN1fZQoaAZoCWgPQwh0Yg/tY8xwQJSGlFKUaBVNOQFoFkdAkQcHH7xd6nV9lChoBmgJaA9DCAEz38FPmm9AlIaUUpRoFU1eAWgWR0CRBzns9jgAdX2UKGgGaAloD0MIu/HuyFhdcUCUhpRSlGgVTQUBaBZHQJEI/fk3juN1fZQoaAZoCWgPQwg0R1Z+mbttQJSGlFKUaBVNNAFoFkdAkQniIHkcTHV9lChoBmgJaA9DCAPQKF06GXFAlIaUUpRoFU0eAWgWR0CRCzyv9tMxdX2UKGgGaAloD0MISYRGsLEWcECUhpRSlGgVTRUBaBZHQJEL3sKLKmt1fZQoaAZoCWgPQwjx1vm3yy9vQJSGlFKUaBVNQAFoFkdAkQv8ZccENnV9lChoBmgJaA9DCPCGNCpw1XFAlIaUUpRoFU0eAWgWR0CRDCB19v0idX2UKGgGaAloD0MIE0VI3U6xcUCUhpRSlGgVTUYBaBZHQJEMmEi+tbN1fZQoaAZoCWgPQwj7ITZY+M5wQJSGlFKUaBVNNgFoFkdAkQy6ekHlfnV9lChoBmgJaA9DCHL6er5mjm1AlIaUUpRoFU0MAWgWR0CRDMPLxI8RdX2UKGgGaAloD0MIWOcYkD1+bkCUhpRSlGgVTSQBaBZHQJEOxsANoal1fZQoaAZoCWgPQwgYk/5eigVtQJSGlFKUaBVNMgFoFkdAkRBUqH4463V9lChoBmgJaA9DCBgmUwUjXW5AlIaUUpRoFU1QAWgWR0CREO8ZDRdAdX2UKGgGaAloD0MI/n+cMGHPcUCUhpRSlGgVTRUBaBZHQJER+KYRdyF1fZQoaAZoCWgPQwiIEFfO3ghxQJSGlFKUaBVNLwFoFkdAkRLKreZXuHV9lChoBmgJaA9DCHDqA8m7l3FAlIaUUpRoFU0UAWgWR0CRE9T2FnIydX2UKGgGaAloD0MIDTM0nggBcUCUhpRSlGgVTSQBaBZHQJEVY078vVV1fZQoaAZoCWgPQwgke4Sa4VBxQJSGlFKUaBVNGwFoFkdAkRcWkFfReHV9lChoBmgJaA9DCGFtjJ0wrXFAlIaUUpRoFU32AWgWR0CRF2E+gUUPdX2UKGgGaAloD0MIaa1ocxzZbkCUhpRSlGgVTSABaBZHQJEXkrxy4nZ1fZQoaAZoCWgPQwjVljrIa1tyQJSGlFKUaBVNFQFoFkdAkReqRhc7hnV9lChoBmgJaA9DCHy2Dg62C3BAlIaUUpRoFU0pAWgWR0CRF8OPvKEGdX2UKGgGaAloD0MIMsueBDbibECUhpRSlGgVTU8BaBZHQJEYfcrRSgp1fZQoaAZoCWgPQwgyyF2E6YpxQJSGlFKUaBVNPgFoFkdAkRk47eVLSXV9lChoBmgJaA9DCLIOR1fpEmxAlIaUUpRoFU1PAWgWR0CRGcxvNu+AdX2UKGgGaAloD0MI4pNOJBjCcUCUhpRSlGgVTVEBaBZHQJEb2/KyOaR1fZQoaAZoCWgPQwiwPbMkwC1wQJSGlFKUaBVNNAFoFkdAkRwLB9Cu2nV9lChoBmgJaA9DCOgtHt7zUmBAlIaUUpRoFU3oA2gWR0CRHQIxQBPsdX2UKGgGaAloD0MIb9kh/mFgUECUhpRSlGgVS9NoFkdAkR1dCE6DG3V9lChoBmgJaA9DCDcz+tHwV2tAlIaUUpRoFU0zAWgWR0CRHabKRuCPdX2UKGgGaAloD0MIJ/bQPpYrcUCUhpRSlGgVTRABaBZHQJEeIkdFOO91fZQoaAZoCWgPQwjz/6ojRylvQJSGlFKUaBVNYQFoFkdAkR5QhbGFSXV9lChoBmgJaA9DCO//44SJcW9AlIaUUpRoFU1HAWgWR0CRHwayKNyYdX2UKGgGaAloD0MIE7ngDL4EcUCUhpRSlGgVTRQBaBZHQJE2GKaXrt51fZQoaAZoCWgPQwiDTZ1HxT9uQJSGlFKUaBVNGwFoFkdAkTapQHiWFHV9lChoBmgJaA9DCDRnfcqxQG9AlIaUUpRoFU0kAWgWR0CRNuoZhrnDdX2UKGgGaAloD0MI73A7NGwCckCUhpRSlGgVTRUBaBZHQJE36avzOHF1fZQoaAZoCWgPQwjcY+lD1yxyQJSGlFKUaBVNVwFoFkdAkTgrqY7aI3V9lChoBmgJaA9DCI+mejL/UEVAlIaUUpRoFUvXaBZHQJE4USSNfgJ1fZQoaAZoCWgPQwixTwDFiHRyQJSGlFKUaBVNEwFoFkdAkTheN1hb4nV9lChoBmgJaA9DCJOmQdF8SHNAlIaUUpRoFU09AWgWR0CROHstkFwDdX2UKGgGaAloD0MIZr0YygmycUCUhpRSlGgVTYsBaBZHQJE6DUExIrh1fZQoaAZoCWgPQwjElEiil5NvQJSGlFKUaBVNBQFoFkdAkTqXWjGkvnV9lChoBmgJaA9DCBKkUuxo2kdAlIaUUpRoFUvnaBZHQJE6p2A5Jbt1fZQoaAZoCWgPQwg34PPDyAxyQJSGlFKUaBVNHgFoFkdAkTvjr7fpEHV9lChoBmgJaA9DCAFtq1nnQXNAlIaUUpRoFU1JAWgWR0CRPQkWRA8kdX2UKGgGaAloD0MIDXGsi5vCckCUhpRSlGgVTXABaBZHQJE9J6X0Gu91fZQoaAZoCWgPQwgR5KCEWTBwQJSGlFKUaBVNJwFoFkdAkT2JpN9H+nV9lChoBmgJaA9DCJMa2gBsD3BAlIaUUpRoFU1CAWgWR0CRQN16E8JVdX2UKGgGaAloD0MI/5WVJqUAcECUhpRSlGgVTZkBaBZHQJFA/nKW9lF1fZQoaAZoCWgPQwhPXfksj2pwQJSGlFKUaBVNOQFoFkdAkUFxzBAOa3V9lChoBmgJaA9DCKyrArWY0G1AlIaUUpRoFU0fAWgWR0CRQjeD3/PxdX2UKGgGaAloD0MI9dkB1xXMa0CUhpRSlGgVTSUBaBZHQJFCumfoRqZ1fZQoaAZoCWgPQwi4rwPnTJNwQJSGlFKUaBVNKQFoFkdAkUK8EV32VXV9lChoBmgJaA9DCH2SO2xiDnFAlIaUUpRoFU07AWgWR0CRQuHNorWidX2UKGgGaAloD0MIELIsmPj2cECUhpRSlGgVTaMBaBZHQJFFhGsmv4d1fZQoaAZoCWgPQwir0EAsG6dxQJSGlFKUaBVNDwFoFkdAkUZlH4Glh3V9lChoBmgJaA9DCCf3OxQF8WxAlIaUUpRoFU1RAWgWR0CRRpeKsMiKdX2UKGgGaAloD0MIg92wbVGca0CUhpRSlGgVTZMBaBZHQJFGxK+SKWN1fZQoaAZoCWgPQwifBDbn4JRyQJSGlFKUaBVNdwFoFkdAkUjT2i+L33V9lChoBmgJaA9DCPJetTIhTXBAlIaUUpRoFU2AAWgWR0CRSUZWq95AdX2UKGgGaAloD0MIB+3Vx8MlcECUhpRSlGgVTS8BaBZHQJFJpuLrHEN1fZQoaAZoCWgPQwj+mNamsfBvQJSGlFKUaBVNPwFoFkdAkUnGdZq20HV9lChoBmgJaA9DCFaDMLd7PG1AlIaUUpRoFU1JAWgWR0CRSe7kGRmsdX2UKGgGaAloD0MIe/Xx0HeBRECUhpRSlGgVS/ZoFkdAkUvzRlYlp3V9lChoBmgJaA9DCIxoO6ZuSnBAlIaUUpRoFU0XAWgWR0CRTUkDZDiPdX2UKGgGaAloD0MInPnVHCCXckCUhpRSlGgVTVABaBZHQJFNz1QIldF1fZQoaAZoCWgPQwivJHmu7xBwQJSGlFKUaBVNMwFoFkdAkU4zVlPJrHV9lChoBmgJaA9DCNPe4AsTyG1AlIaUUpRoFU1AAWgWR0CRTj4UeuFIdX2UKGgGaAloD0MIsistI/U+R0CUhpRSlGgVS/VoFkdAkU6CWzF+/nV9lChoBmgJaA9DCKfqHtlc1XBAlIaUUpRoFU19AWgWR0CRT1ornTy8dX2UKGgGaAloD0MIi1BsBc3YcUCUhpRSlGgVTXgBaBZHQJFPniwSrYJ1fZQoaAZoCWgPQwgUP8bcNWpzQJSGlFKUaBVNFQFoFkdAkVBg1FYuCnV9lChoBmgJaA9DCM8wtaUOSk5AlIaUUpRoFUvIaBZHQJFQiRRuTA51fZQoaAZoCWgPQwgX1SKiGGNvQJSGlFKUaBVNBgFoFkdAkVITej2zwHV9lChoBmgJaA9DCO25TE2CmnBAlIaUUpRoFU1XAWgWR0CRUmhgmZ3LdX2UKGgGaAloD0MIF4IclLCyb0CUhpRSlGgVTQYBaBZHQJFSxNN8E3d1fZQoaAZoCWgPQwioixTKwk1vQJSGlFKUaBVNXgFoFkdAkVLjqW1MNHV9lChoBmgJaA9DCAKetHDZxm9AlIaUUpRoFU0jAWgWR0CRU1mNR3vAdX2UKGgGaAloD0MInyEcs+w/bkCUhpRSlGgVTUMBaBZHQJFTvoyKvV51fZQoaAZoCWgPQwiMoDGTqGNAQJSGlFKUaBVL1mgWR0CRVNN9ph4MdX2UKGgGaAloD0MI5nYv98kNOUCUhpRSlGgVS/1oFkdAkVWXpOerdXV9lChoBmgJaA9DCJSilXtBfnJAlIaUUpRoFU1nAWgWR0CRWALhaTwEdX2UKGgGaAloD0MI6Q5iZwoNGkCUhpRSlGgVS+hoFkdAkVgscIZ62XV9lChoBmgJaA9DCDONJhdj13BAlIaUUpRoFU02AWgWR0CRWH+tKZlWdX2UKGgGaAloD0MInPhqR7EDckCUhpRSlGgVTRABaBZHQJFYjEl3Qld1fZQoaAZoCWgPQwgF3zR99nRwQJSGlFKUaBVNMgFoFkdAkViptm+TNnV9lChoBmgJaA9DCJXwhF7/bm1AlIaUUpRoFU0gAWgWR0CRWNB7eEZjdWUu"
+    },
+    "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-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a3dee12b2f64259c625239359ee6ae705a33d85062f6743debcff21c31ac4128
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:433e1491bf19d5c78c873a69b2db573b1871e2369f6ffa991999f82fd0790774
+size 43201

ppo-LunarLander-v2/pytorch_variables.pth

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

ppo-LunarLander-v2/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": 248.62887548755498, "std_reward": 20.69727743646556, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-25T15:05:29.988022"}