My third try

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: 270.44 +/- 12.82
+      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 0x78536f5f35b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78536f5f3640>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78536f5f36d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78536f5f3760>", "_build": "<function ActorCriticPolicy._build at 0x78536f5f37f0>", "forward": "<function ActorCriticPolicy.forward at 0x78536f5f3880>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78536f5f3910>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78536f5f39a0>", "_predict": "<function ActorCriticPolicy._predict at 0x78536f5f3a30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78536f5f3ac0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78536f5f3b50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78536f5f3be0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78537918e040>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1209600, "_total_timesteps": 1200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1726728512992945691, "learning_rate": 0.0003, "tensorboard_log": null, "_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": -0.008000000000000007, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVPgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGJGanJkoWqMAWyUTegDjAF0lEdAmVwQlruYyHV9lChoBkdAYmP1bqyGBWgHTegDaAhHQJljMBgeA/d1fZQoaAZHQGRIS/bj94xoB03oA2gIR0CZZrmh/RVqdX2UKGgGR0A/z3yqdYnwaAdL8mgIR0CZamYUFjd6dX2UKGgGR0BbyyudPLxJaAdN6ANoCEdAmXAudXko4XV9lChoBkdAZZfeWOZLI2gHTegDaAhHQJl3gefZmI11fZQoaAZHQGQNvmPo3aVoB03oA2gIR0CZecjQiRnwdX2UKGgGR0BhgCAQQL/kaAdN6ANoCEdAmY4uHnEET3V9lChoBkdAZ2XkRzzVc2gHTegDaAhHQJmUoGcFyJd1fZQoaAZHQGJEfTspobpoB03oA2gIR0CZlRRwIdELdX2UKGgGR0Bi7aDZlFtsaAdN6ANoCEdAmZsN7jT8YXV9lChoBkdAZUXe3QUpNWgHTegDaAhHQJmctYkmhM91fZQoaAZHQGNsQMx46fdoB03oA2gIR0CZnWJxeb/fdX2UKGgGR0BoJzR8c+7laAdN6ANoCEdAmaARWYF7lnV9lChoBkdAZNXfAKv3amgHTegDaAhHQJmiP+YMOPN1fZQoaAZHQGOPWszVMEloB03oA2gIR0CZox3gDRtxdX2UKGgGR0BiRpKe05U+aAdN6ANoCEdAmaYm8RL9M3V9lChoBkdAYSI9zwMH8mgHTegDaAhHQJnKLpxFRYR1fZQoaAZHQGD+0/GEPDpoB03oA2gIR0CZzacTJyQxdX2UKGgGR0Bx7Vsl9jPOaAdNcQFoCEdAmdDFirksBnV9lChoBkdAZ5sTJyQxOGgHTegDaAhHQJnRKSfUWmB1fZQoaAZHQGNRVjRUm2NoB03oA2gIR0CZ1jhzvJA/dX2UKGgGR0BiSjXYlIEsaAdN6ANoCEdAmdzdgv114nV9lChoBkdAYSaYJmdy1mgHTegDaAhHQJneY+iaiK11fZQoaAZHQHC8BxHXmNloB02RAmgIR0CZ68SQo1DTdX2UKGgGR0BgwI/C66J7aAdN6ANoCEdAmfLBQaaTfXV9lChoBkdAYSDGR3eN1mgHTegDaAhHQJn4d7iQ1aZ1fZQoaAZHQGJwrVvuPWBoB03oA2gIR0CZ+N8kD6nBdX2UKGgGR0BnH65NGmUGaAdN6ANoCEdAmf5Ppt78enV9lChoBkdAZvQhzNliB2gHTegDaAhHQJn/x+6RQrN1fZQoaAZHQGQj2+GoJiRoB03oA2gIR0CaBXAeJYT1dX2UKGgGR0BmZmKl54W2aAdN6ANoCEdAmgZgaaTfSHV9lChoBkdAPVfS+g13uGgHS/BoCEdAmgdJxrBTGnV9lChoBkdAKanfMwDeTGgHTQABaAhHQJoIovEjxCp1fZQoaAZHQGeeXWFvhqFoB03oA2gIR0CaCW8h9srNdX2UKGgGR0Bc/2Ya5wwTaAdN6ANoCEdAmg/lCw8nu3V9lChoBkdAX6Ro6CDmKmgHTegDaAhHQJoS1cRlHz91fZQoaAZHQGLzSq+8Gs5oB03oA2gIR0CaFs5e7cwhdX2UKGgGR0BjodJxvNu+aAdN6ANoCEdAmhdXGOuJUHV9lChoBkdAYmMTAWSEDmgHTegDaAhHQJo4TaQFLWZ1fZQoaAZHQHCxOXAuZkVoB03TAWgIR0CaOKsN2C/XdX2UKGgGR0Bi4GFN+LFXaAdN6ANoCEdAmj3UMw1zhnV9lChoBkdAZeiHoHLRr2gHTegDaAhHQJo/JfLLZBd1fZQoaAZHQFB8Qkona39oB0vfaAhHQJpGi/9Hc1x1fZQoaAZHQGCC7sWweNloB03oA2gIR0CaR/o4MnZ1dX2UKGgGR0BnanfbblBAaAdN6ANoCEdAmlEjc2zfJnV9lChoBkdAYqCg9vCMxWgHTegDaAhHQJpfCRr8BMl1fZQoaAZHQGWf6n752yNoB03oA2gIR0CaaC2g3974dX2UKGgGR0BoFklsxfv4aAdN6ANoCEdAmmlK2SdOI3V9lChoBkdAZozlCCz1LGgHTegDaAhHQJpqe08eS0V1fZQoaAZHQGdlgo5PuXxoB03oA2gIR0CabAxAB1cMdX2UKGgGR0BgDhdY4hllaAdN6ANoCEdAmmzxIFvAGnV9lChoBkdAZRaNrCWNWGgHTegDaAhHQJp0V+H8CPp1fZQoaAZHQGTYe8f3evZoB03oA2gIR0Cad8pDNQj2dX2UKGgGR0BdvzX4CZF5aAdN6ANoCEdAmnq4+0PYnXV9lChoBkdAZtcZQYUFjmgHTegDaAhHQJp7F4TsY2t1fZQoaAZHQGWoA13t8eFoB03oA2gIR0CagL7EYO2BdX2UKGgGR0BkmKr7wazeaAdN6ANoCEdAmokKi48U23V9lChoBkdAYI91gYxcmmgHTegDaAhHQJqKlKe05U91fZQoaAZHQGAN+yRjjJdoB03oA2gIR0CaqycS5AhTdX2UKGgGR0Bj18SVW0Z4aAdN6ANoCEdAmqx3eWOZLXV9lChoBkdAZSnwTdtVJmgHTegDaAhHQJqyvY/Vy3l1fZQoaAZHQCijfixVyWBoB00PAWgIR0Cav3XRgJC0dX2UKGgGR0BhMxJ2+wkgaAdN6ANoCEdAmsCPQjUutnV9lChoBkdAZouVPepGWmgHTegDaAhHQJrH9OKwY+B1fZQoaAZHQGkczjWCmMxoB03oA2gIR0CayOtITXardX2UKGgGR0BhrOZZ0SyuaAdN6ANoCEdAmsnuDnNgSnV9lChoBkdAXKkTbnHNo2gHTegDaAhHQJrLPG5tm+V1fZQoaAZHQGK1CUxEfDFoB03oA2gIR0CazC82Jiy6dX2UKGgGR0Bi5tnh86V/aAdN6ANoCEdAmtKai48U23V9lChoBkdAZrgYiPhhpmgHTegDaAhHQJrV2IDYAbR1fZQoaAZHQGCLpEYwZfloB03oA2gIR0Ca2OTrmhdudX2UKGgGR0BmXSMaS9uhaAdN6ANoCEdAmtlIVuaWonV9lChoBkdAYc9dM0xdp2gHTegDaAhHQJreQCxNZeR1fZQoaAZHQGP0y6lLvkRoB03oA2gIR0Ca5KuOjqOcdX2UKGgGR0BgNzAYYR/WaAdN6ANoCEdAmuaBHG0eEXV9lChoBkdAXvMP8Q7LdWgHTegDaAhHQJry/PPcBU91fZQoaAZHQGE+bH6uW8hoB03oA2gIR0Ca+lYGMXJpdX2UKGgGR0Bii+xD9fkWaAdN6ANoCEdAmyIB+vyLAHV9lChoBkdAX+cXizcAR2gHTegDaAhHQJsjql0o0AN1fZQoaAZHQG0nO2RaHKxoB025A2gIR0CbKoyTY/VzdX2UKGgGR0BjbayjYZl4aAdN6ANoCEdAmyzON1hb4nV9lChoBkdAXHWkAPuogmgHTegDaAhHQJsvBCw8nu11fZQoaAZHQGYdgkcCHRFoB03oA2gIR0CbMInb7CSBdX2UKGgGR0BgQijQAuIzaAdN6ANoCEdAmzFsS5AhS3V9lChoBkdAYqhdYW+GoWgHTegDaAhHQJs40i8nNPh1fZQoaAZHQGUCz5oGpuNoB03oA2gIR0CbPDB91EE1dX2UKGgGR0BQcl0PpY9xaAdLzWgIR0CbPnELH+6zdX2UKGgGR0BlNcgZCOWCaAdN6ANoCEdAmz8a1Cw8n3V9lChoBkdAYq8u6ErXlWgHTegDaAhHQJs/hcSoOx11fZQoaAZHQGRvbSZ0CBBoB03oA2gIR0CbRFjENvwWdX2UKGgGR0Bm6CKLsKLLaAdN6ANoCEdAm0op8BuGbnV9lChoBkdAZoB0AcT8HmgHTegDaAhHQJtLpVENOM51fZQoaAZHQGHGWFWXC0poB03oA2gIR0CbVpLZzxPPdX2UKGgGR0BIiCxVyWAxaAdL22gIR0CbXhhy8zyjdX2UKGgGR0BiaykZaV2SaAdN6ANoCEdAm17Yoy9EkXV9lChoBkdALFHhCMPz4GgHS/5oCEdAm18Bl6JIlXV9lChoBkdAcVEs6JZW72gHTTsDaAhHQJtpC2x6fJ51fZQoaAZHQGDXD/dZaFFoB03oA2gIR0CbaZRGc4HYdX2UKGgGR0BhQ3OGCZndaAdN6ANoCEdAm2qZBTn7pHVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 252, "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": 1200, "gamma": 0.9992, "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:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2_dkv4.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dc8487f5c8615d27498f8da4f0316b6aaaa91d0c99a04622ec1db77b96b792e3
+size 148081

ppo-LunarLander-v2_dkv4/_stable_baselines3_version

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

ppo-LunarLander-v2_dkv4/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 0x78536f5f35b0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78536f5f3640>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78536f5f36d0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78536f5f3760>",
+        "_build": "<function ActorCriticPolicy._build at 0x78536f5f37f0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x78536f5f3880>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78536f5f3910>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78536f5f39a0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x78536f5f3a30>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78536f5f3ac0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78536f5f3b50>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78536f5f3be0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x78537918e040>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1209600,
+    "_total_timesteps": 1200000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1726728512992945691,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_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": -0.008000000000000007,
+    "_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": 252,
+    "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": 1200,
+    "gamma": 0.9992,
+    "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:": "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"
+    }
+}

ppo-LunarLander-v2_dkv4/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:acae2fb44beee8f253727b0ae18a07694ef81b991a20ca8aae56a9eb8c0e7892
+size 88362

ppo-LunarLander-v2_dkv4/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:59c5d9165abd2a3f0c5204afb8e2379e96c1a76283c54e7d66e0e2ad2a2609f3
+size 43762

ppo-LunarLander-v2_dkv4/pytorch_variables.pth

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

ppo-LunarLander-v2_dkv4/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.4.0+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 270.4441289, "std_reward": 12.816620789137126, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-19T07:21:25.477572"}