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: 269.05 +/- 7.49
+      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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7906252404c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x790625240550>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7906252405e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x790625240670>", "_build": "<function ActorCriticPolicy._build at 0x790625240700>", "forward": "<function ActorCriticPolicy.forward at 0x790625240790>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x790625240820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7906252408b0>", "_predict": "<function ActorCriticPolicy._predict at 0x790625240940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7906252409d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x790625240a60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x790625240af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7906251e3f40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716019933238246497, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAG0qLr7VYxM/1aUqPs5Zfr4ddfw88CJ9PQAAAAAAAAAAmgH1PNhutD+uTqk9n+iivjpm5j2kjzs9AAAAAAAAAAAzP8U8ww0BumgGVrnE+h6zlHsvuwClezgAAIA/AACAP20RbT6SE+g+GwmTvvvXZ77jvk29btdVPAAAAAAAAAAAGt1jPri+gz/KLi8+viezvm9Iiz4u9ae9AAAAAAAAAACAP3G9SIeNutRqqDQPXe8vfc/AuXt0TLMAAIA/AACAP2YOMbwp2Hq6W3rEu1rM+Dcn/K26SjHptgAAgD8AAIA/jVSFPY8OSromIla7cw/WN1YvpDrH1BE6AACAPwAAAAAzY4C9e8qourUwaTpAAFM1OYgZudrBhbkAAIA/AACAP+ZYEr4GY48/iOR/vl0dsr6Apoq+jlo9uwAAAAAAAAAATStSPktXTD9WXgE8kA6LvpHUGz5kMka9AAAAAAAAAACzdZ69x7oEPwRVKj7zcJe+RRqfPSvKx70AAAAAAAAAAPNvjb324FK6/n+Bt+KTR7LobPa6ABSYNgAAgD8AAIA/APvXPXQ/kz8YZr4+oBfHvu6z+z3Cc08+AAAAAAAAAAAGpTy+v/mSP2aro74ErL2+nf6evhrlZb0AAAAAAAAAANLyir6WWi8/othAvJ0Apr4AMzi+zOAtPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:039f6c788eb64c10079af51539e03e482d9c13e72e12730626ea110c660ec236
+size 148086

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7906252404c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x790625240550>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7906252405e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x790625240670>",
+        "_build": "<function ActorCriticPolicy._build at 0x790625240700>",
+        "forward": "<function ActorCriticPolicy.forward at 0x790625240790>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x790625240820>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7906252408b0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x790625240940>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7906252409d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x790625240a60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x790625240af0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7906251e3f40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000.0,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1716019933238246497,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAG0qLr7VYxM/1aUqPs5Zfr4ddfw88CJ9PQAAAAAAAAAAmgH1PNhutD+uTqk9n+iivjpm5j2kjzs9AAAAAAAAAAAzP8U8ww0BumgGVrnE+h6zlHsvuwClezgAAIA/AACAP20RbT6SE+g+GwmTvvvXZ77jvk29btdVPAAAAAAAAAAAGt1jPri+gz/KLi8+viezvm9Iiz4u9ae9AAAAAAAAAACAP3G9SIeNutRqqDQPXe8vfc/AuXt0TLMAAIA/AACAP2YOMbwp2Hq6W3rEu1rM+Dcn/K26SjHptgAAgD8AAIA/jVSFPY8OSromIla7cw/WN1YvpDrH1BE6AACAPwAAAAAzY4C9e8qourUwaTpAAFM1OYgZudrBhbkAAIA/AACAP+ZYEr4GY48/iOR/vl0dsr6Apoq+jlo9uwAAAAAAAAAATStSPktXTD9WXgE8kA6LvpHUGz5kMka9AAAAAAAAAACzdZ69x7oEPwRVKj7zcJe+RRqfPSvKx70AAAAAAAAAAPNvjb324FK6/n+Bt+KTR7LobPa6ABSYNgAAgD8AAIA/APvXPXQ/kz8YZr4+oBfHvu6z+z3Cc08+AAAAAAAAAAAGpTy+v/mSP2aro74ErL2+nf6evhrlZb0AAAAAAAAAANLyir6WWi8/othAvJ0Apr4AMzi+zOAtPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c77faa80befc49e93d4ef91a4dd1dfeca5eff71124691dc5e54ef05dbbf1f2f9
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f22f316873f562a204c8d671dcf5f60d0c9c2330cbb5226887261a78372bbb60
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.2.1+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 269.05239736741885, "std_reward": 7.489577975519297, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-18T08:53:37.871331"}