Upload PPO agent for Unit 1: 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: 253.94 +/- 25.34
+      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 0x7f7cb590bca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7cb590bd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7cb590bdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7cb590be50>", "_build": "<function ActorCriticPolicy._build at 0x7f7cb590bee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f7cb590bf70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7cb590f040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7cb590f0d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7cb590f160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7cb590f1f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7cb590f280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7cb59084b0>"}, "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": 1671347433074779331, "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 sha256:5f8cc2fefacc6e7b456460724fcc2bb670fc729474970a41b139451ce872cc5a
+size 147210

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 0x7f7cb590bca0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7cb590bd30>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7cb590bdc0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7cb590be50>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f7cb590bee0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f7cb590bf70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7cb590f040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f7cb590f0d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7cb590f160>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7cb590f1f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7cb590f280>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f7cb59084b0>"
+    },
+    "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": 1671347433074779331,
+    "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:": "gAWVehAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI9gt2w/aBckCUhpRSlIwBbJRNggGMAXSUR0CcRErWRRuTdX2UKGgGaAloD0MI2q1lMpxDbkCUhpRSlGgVTU0BaBZHQJxEsi7kGRp1fZQoaAZoCWgPQwjq6SPwh/VBQJSGlFKUaBVNCQFoFkdAnES7MX7+DXV9lChoBmgJaA9DCOC7zRsnGT5AlIaUUpRoFUvvaBZHQJxFPvttygh1fZQoaAZoCWgPQwj2XKYmgTdwQJSGlFKUaBVNtgFoFkdAnEZm6shgV3V9lChoBmgJaA9DCCoaa3/nMnFAlIaUUpRoFU1WAWgWR0CcRqoScslLdX2UKGgGaAloD0MII0p7g6+XbECUhpRSlGgVTYgCaBZHQJxLAL/jsD51fZQoaAZoCWgPQwhNLVvri3FwQJSGlFKUaBVNRAFoFkdAnEup31SOznV9lChoBmgJaA9DCAwG19xRGnFAlIaUUpRoFU1NAWgWR0CcTBk/KQq7dX2UKGgGaAloD0MI3qzB+2pbcUCUhpRSlGgVTUABaBZHQJxfpzPrv9d1fZQoaAZoCWgPQwj0Fg/vuXFuQJSGlFKUaBVNdAFoFkdAnF/gSJ0nxHV9lChoBmgJaA9DCPuT+NxJiXBAlIaUUpRoFU0mAWgWR0CcYH25xzaLdX2UKGgGaAloD0MISuza3i5RcECUhpRSlGgVTVgBaBZHQJxhxaB7NSt1fZQoaAZoCWgPQwjbiCe7WVFwQJSGlFKUaBVNPAFoFkdAnGNxufmLcnV9lChoBmgJaA9DCJ6ZYDiXbHJAlIaUUpRoFU00AWgWR0CcY+OjZcs2dX2UKGgGaAloD0MIqOMxAxX+cECUhpRSlGgVTVcBaBZHQJxkjX05EMN1fZQoaAZoCWgPQwj6KCMugGltQJSGlFKUaBVNOgFoFkdAnGV94RmK7HV9lChoBmgJaA9DCDhJ88f0fHFAlIaUUpRoFU1vAWgWR0CcZ8YFaB7NdX2UKGgGaAloD0MIN/sD5bZwUECUhpRSlGgVS/BoFkdAnGgd3wCr93V9lChoBmgJaA9DCJnTZTFxaHJAlIaUUpRoFU1VAWgWR0Ccaw/XXiBHdX2UKGgGaAloD0MIDfs9sU7QcUCUhpRSlGgVTR4CaBZHQJxrk8IRh+h1fZQoaAZoCWgPQwg+z582KqVqQJSGlFKUaBVNVwFoFkdAnGu3WFvhqHV9lChoBmgJaA9DCDylg/V/I25AlIaUUpRoFU2aAmgWR0CcbDoc7yQQdX2UKGgGaAloD0MIYviImBJDcUCUhpRSlGgVTVYBaBZHQJxsskmhM8J1fZQoaAZoCWgPQwjO4sXCkExyQJSGlFKUaBVNUwFoFkdAnGzEL6UJOXV9lChoBmgJaA9DCI//AkGAV1FAlIaUUpRoFUv+aBZHQJxs9lMAWBV1fZQoaAZoCWgPQwjutDUiGLpTQJSGlFKUaBVN6ANoFkdAnG0l9F4LTnV9lChoBmgJaA9DCNi2KLMB9HFAlIaUUpRoFU0PAWgWR0CcbcMZP2wndX2UKGgGaAloD0MIO1PovMaYQkCUhpRSlGgVS/5oFkdAnG3KEeyRjnV9lChoBmgJaA9DCJbMsbyrNktAlIaUUpRoFUv4aBZHQJxuREG7jDN1fZQoaAZoCWgPQwjpQxfU99FwQJSGlFKUaBVNiQFoFkdAnG6sSGrS3XV9lChoBmgJaA9DCOCFrdnKFm5AlIaUUpRoFU2ZAWgWR0Ccb+njQzDXdX2UKGgGaAloD0MIb7w7MlY5cUCUhpRSlGgVTT8BaBZHQJxx1aY/mkp1fZQoaAZoCWgPQwjt2AjE62pvQJSGlFKUaBVNOgFoFkdAnHTthuwX7HV9lChoBmgJaA9DCGlTdY9sXG1AlIaUUpRoFU3IA2gWR0CcdO0uDjBEdX2UKGgGaAloD0MIRWYucLmucECUhpRSlGgVTZgBaBZHQJx1n+98JD51fZQoaAZoCWgPQwivk/qyNFByQJSGlFKUaBVNJgFoFkdAnHXvddmg8XV9lChoBmgJaA9DCOOo3EQtBm1AlIaUUpRoFU02AWgWR0CcdgOlwcYJdX2UKGgGaAloD0MIqAAYz6CxMsCUhpRSlGgVS/hoFkdAnHbk3juKGnV9lChoBmgJaA9DCIQNT6+UFTpAlIaUUpRoFU0mAWgWR0Ccd0SJCSiedX2UKGgGaAloD0MIoIobtxi7bUCUhpRSlGgVTU8BaBZHQJx39fCyhSN1fZQoaAZoCWgPQwh7hJohVUdvQJSGlFKUaBVNYgFoFkdAnHgyRfWtl3V9lChoBmgJaA9DCE94CU59yXBAlIaUUpRoFU2PAWgWR0CceKoZhrnDdX2UKGgGaAloD0MIS5NS0K0icECUhpRSlGgVTaYBaBZHQJx5TJNj9XN1fZQoaAZoCWgPQwg0LhwISWttQJSGlFKUaBVNbwFoFkdAnHmsJIDoyXV9lChoBmgJaA9DCCttcY2POXBAlIaUUpRoFU0vAWgWR0Ccej/47A+IdX2UKGgGaAloD0MIUTHO38RtcUCUhpRSlGgVTakBaBZHQJx6fK+zt1J1fZQoaAZoCWgPQwg7cTleQTBwQJSGlFKUaBVNrwFoFkdAnHvtat9x63V9lChoBmgJaA9DCEzD8BGx229AlIaUUpRoFU06AWgWR0CcfGEeQuEmdX2UKGgGaAloD0MIOGkaFM1cb0CUhpRSlGgVTTEBaBZHQJx+ztF8XvZ1fZQoaAZoCWgPQwiCx7d3jahwQJSGlFKUaBVNKAFoFkdAnH92Q8wHq3V9lChoBmgJaA9DCEgxQKIJp29AlIaUUpRoFU1RAWgWR0CcgB2CNCJGdX2UKGgGaAloD0MIQQ5KmGmqbECUhpRSlGgVTXoBaBZHQJyVqShakh11fZQoaAZoCWgPQwjEmPT3kpVwQJSGlFKUaBVNSAFoFkdAnJYZrP+n63V9lChoBmgJaA9DCMVU+glnzGxAlIaUUpRoFU1uAWgWR0Ccli7V8Ti9dX2UKGgGaAloD0MI9s/TgEGpcUCUhpRSlGgVTVQBaBZHQJyXK1SflIV1fZQoaAZoCWgPQwhG66hqAtJwQJSGlFKUaBVNuQFoFkdAnJfiXIEKV3V9lChoBmgJaA9DCPg1kgThoW1AlIaUUpRoFU2IAWgWR0CcmGlHz6JqdX2UKGgGaAloD0MISUikbfywbUCUhpRSlGgVTTgBaBZHQJyYk8yN4qx1fZQoaAZoCWgPQwiGkzR/TJFvQJSGlFKUaBVNXAFoFkdAnJi9grpaBHV9lChoBmgJaA9DCLK8qx6wlG1AlIaUUpRoFU24AWgWR0CcmVxFy7wsdX2UKGgGaAloD0MIC7jn+VOScECUhpRSlGgVTYoBaBZHQJyZyAvtdAx1fZQoaAZoCWgPQwgSvvc3aIZwQJSGlFKUaBVNNAFoFkdAnJoZGWldknV9lChoBmgJaA9DCJF7urojLXFAlIaUUpRoFU2AAWgWR0Ccmnf3vhIfdX2UKGgGaAloD0MItqLNca5Rc0CUhpRSlGgVS/toFkdAnJtWOU+s5nV9lChoBmgJaA9DCBu9GqD0SHBAlIaUUpRoFU1eAWgWR0Ccngah6By0dX2UKGgGaAloD0MIiJy+ni/fbkCUhpRSlGgVTUABaBZHQJyeHFQ2uPp1fZQoaAZoCWgPQwhVUFH1q2VyQJSGlFKUaBVNCQFoFkdAnJ6FEVnEl3V9lChoBmgJaA9DCP5g4Lk32XBAlIaUUpRoFU0aAWgWR0Ccn48fV7QcdX2UKGgGaAloD0MIwHtHjQlROECUhpRSlGgVTQ8BaBZHQJygBpcophF1fZQoaAZoCWgPQwjUghd9BbBwQJSGlFKUaBVNEQFoFkdAnKC+/tY0VXV9lChoBmgJaA9DCNP6WwJwOHBAlIaUUpRoFU1nAWgWR0CcolUsFt9AdX2UKGgGaAloD0MIHT1+b1MPb0CUhpRSlGgVTS8BaBZHQJyiXx3FDOV1fZQoaAZoCWgPQwhQUmABTEJvQJSGlFKUaBVNPAFoFkdAnKMFspG4JHV9lChoBmgJaA9DCP5fdeSIknBAlIaUUpRoFU0eAWgWR0Cco1j7yhBadX2UKGgGaAloD0MI7IUCtgOLb0CUhpRSlGgVTVABaBZHQJyj4+0PYnR1fZQoaAZoCWgPQwiGqwMgboBwQJSGlFKUaBVNWwFoFkdAnKTq24NI9XV9lChoBmgJaA9DCN5zYDlCN21AlIaUUpRoFU1RAWgWR0Ccpdhx5s0pdX2UKGgGaAloD0MInUfF/51CcECUhpRSlGgVTYgCaBZHQJymAFY+0PZ1fZQoaAZoCWgPQwiDvvT252RrQJSGlFKUaBVNZAFoFkdAnKYHBtUGV3V9lChoBmgJaA9DCEhvuI+chXBAlIaUUpRoFU0+AWgWR0CcpjoYNy5qdX2UKGgGaAloD0MI0AoMWV2EcUCUhpRSlGgVTTQBaBZHQJyoUQFs54p1fZQoaAZoCWgPQwiWd9UD5j9uQJSGlFKUaBVNNgFoFkdAnKhOOXE61nV9lChoBmgJaA9DCEImGTkL7GxAlIaUUpRoFU1OAWgWR0CcqrPnSv1UdX2UKGgGaAloD0MIemzLgDPjbUCUhpRSlGgVTVABaBZHQJyrRZMcp9Z1fZQoaAZoCWgPQwjbiZKQyMZwQJSGlFKUaBVNaAFoFkdAnK0W43FUAHV9lChoBmgJaA9DCLJJfsQv5HFAlIaUUpRoFU1DAWgWR0CcrWAuqWC3dX2UKGgGaAloD0MIcHoX74cDcECUhpRSlGgVTa8BaBZHQJytfvphWo51fZQoaAZoCWgPQwjlnUMZ6tRxQJSGlFKUaBVNUgFoFkdAnK3lqveP73V9lChoBmgJaA9DCO/KLhhcuG9AlIaUUpRoFU1CAWgWR0CcrfhnanJldX2UKGgGaAloD0MIG5/J/rlhcUCUhpRSlGgVTUkBaBZHQJyugUXYUWV1fZQoaAZoCWgPQwi0HykiAxFxQJSGlFKUaBVNcgFoFkdAnLCBUrCm/HV9lChoBmgJaA9DCL3hPnIrPnBAlIaUUpRoFU0zAWgWR0CcsOY9gWrPdX2UKGgGaAloD0MI8WWiCKmCcECUhpRSlGgVTWoBaBZHQJyxXbItDlZ1fZQoaAZoCWgPQwip91RO++dtQJSGlFKUaBVNSgFoFkdAnLFoAjps43V9lChoBmgJaA9DCEP/BBdrxnFAlIaUUpRoFU1NAWgWR0CcsYSi/O+qdX2UKGgGaAloD0MI2ozTEFUVckCUhpRSlGgVTTUBaBZHQJyzQQPI4l11fZQoaAZoCWgPQwhKzok9NMdrQJSGlFKUaBVNRwFoFkdAnLPSC4Bmw3V9lChoBmgJaA9DCGwJ+aBndG1AlIaUUpRoFU2lAWgWR0Ccs/jxCpm3dX2UKGgGaAloD0MInQ5kPbXXcUCUhpRSlGgVTRoBaBZHQJy214qwyIp1ZS4="
+    },
+    "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:f6347ac3336fbe51b49e8a55e48cc61072d449d0c9a134cea960282e6dac44a9
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f67882289c6cb100960656a24abe57c9444d1f573138383cc8e59930b7d0f0c1
+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": 253.94393424994342, "std_reward": 25.33889483048267, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-18T07:49:12.127693"}