Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 265.63 +/- 12.77
+      value: -24.95 +/- 112.58
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +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 0x7f9ca4450ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9ca4450d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9ca4450dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9ca4450e50>", "_build": "<function ActorCriticPolicy._build at 0x7f9ca4450ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f9ca4450f70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9ca4451000>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9ca4451090>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9ca4451120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9ca44511b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9ca4451240>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9ca44512d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f9ca4449e80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687713571217589716, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM2+Sb1ck2y6sMH4OIk75jPx2186H9MRuAAAgD8AAIA/mu63PXselLrBhI67YKYtOLSsibpwiOY3AACAPwAAgD+msuK9K7/dPf6gRT6HK3y+2gpxPdrJiD0AAAAAAAAAAM04F73s6au5BOGKOjUNGTV3WyS6q7WguQAAgD8AAIA/8y3YvcPZDbp3EDM3LzUfMsFfujmNCFe2AACAPwAAgD/N0g49pEBJucVd8brmFge1T4JRup6cDjoAAIA/AACAP5obHr0pEFi6xZGrum1OoLV/1Lo6xQbKOQAAgD8AAIA/Gu6WvRRYi7pRNJS6QCY5tXkkpDnhiKo5AACAPwAAgD8GRQE+tr0TvFYWSL5WPoK8X7CvPXp2VrwAAIA/AACAP81UEL2P8im6I/vEus6HW7ZpBiE7O3vlOQAAgD8AAIA/pherPhJnZD8YS5+9fL/jvjLrmj5BGKW+AAAAAAAAAAAanty9dGaSvPCGTz6FvyG8KSYDPmrhAz0AAIA/AACAP7OggL0U5I+6Gj3mOt7SHDYaFkQ7LtsDugAAgD8AAIA/GsYsveG+hT/w6cm998/EvgWJLr1lxn48AAAAAAAAAAAAP6C8w4FQuqbmn7qxCaQ1kYxkO8UhuzkAAIA/AACAPxP6ST5Is6c/ONrDPsGg0b5IvCA+ZIuQPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"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 0x78868a3ebe20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78868a3ebeb0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78868a3ebf40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78868a3f4040>", "_build": "<function ActorCriticPolicy._build at 0x78868a3f40d0>", "forward": "<function ActorCriticPolicy.forward at 0x78868a3f4160>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78868a3f41f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78868a3f4280>", "_predict": "<function ActorCriticPolicy._predict at 0x78868a3f4310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78868a3f43a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78868a3f4430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78868a3f44c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78868a38dd80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711290674316075318, "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": -0.1468799999999999, "_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": 28, "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:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "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

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0219f47854040f42c8f4c1607823623d75092bb1c6475260f66eb42bdef2e782
-size 146755
+oid sha256:e669f923db862658b91d94a876c09cb0a57ececd0c53f2e39bf849c69e15e1e2
+size 147947

ppo-LunarLander-v2/data

@@ -4,34 +4,34 @@
         ":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 0x7f9ca4450ca0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9ca4450d30>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9ca4450dc0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9ca4450e50>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f9ca4450ee0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f9ca4450f70>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9ca4451000>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9ca4451090>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f9ca4451120>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9ca44511b0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9ca4451240>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9ca44512d0>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x78868a3ebe20>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78868a3ebeb0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78868a3ebf40>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78868a3f4040>",
+        "_build": "<function ActorCriticPolicy._build at 0x78868a3f40d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x78868a3f4160>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78868a3f41f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78868a3f4280>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x78868a3f4310>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78868a3f43a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78868a3f4430>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78868a3f44c0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f9ca4449e80>"
+        "_abc_impl": "<_abc._abc_data object at 0x78868a38dd80>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 114688,
+    "_total_timesteps": 100000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1687713571217589716,
+    "start_time": 1711290674316075318,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,20 +41,20 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.1468799999999999,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
+    "_n_updates": 28,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
-        ":serialized:": "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",
+        ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
         "dtype": "float32",
         "bounded_below": "[ True  True  True  True  True  True  True  True]",
         "bounded_above": "[ True  True  True  True  True  True  True  True]",
@@ -69,7 +69,7 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-        ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
+        ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
         "n": "4",
         "start": "0",
         "_shape": [],

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:413485dbf5696ebbc752dfc4503c4ee46bac009823236b551564384a67c72c49
-size 87929
+oid sha256:c5813847361768a54b90a3500890d5cfa1713e36fbdcff91a8e1e617f0e83766
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b38278d1cd785b11e3768879a07e0b236ec6820f7c11afd94ea6788610471ba1
-size 43329
+oid sha256:35e16f3f8a385c3bdafcd828a8eb23abf0fa29fc9cfcabc108a113c7f8069176
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
-size 431
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -1,9 +1,9 @@
-- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
 - Python: 3.10.12
 - Stable-Baselines3: 2.0.0a5
-- PyTorch: 2.0.1+cu118
+- PyTorch: 2.2.1+cu121
 - GPU Enabled: True
-- Numpy: 1.22.4
+- Numpy: 1.25.2
 - Cloudpickle: 2.2.1
 - Gymnasium: 0.28.1
 - OpenAI Gym: 0.25.2

results.json

@@ -1 +1 @@
-{"mean_reward": 265.632846470137, "std_reward": 12.774117521838164, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-25T18:17:05.838632"}
+{"mean_reward": -24.94595976100827, "std_reward": 112.58255416677083, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-24T14:35:43.086344"}