second upload of PPO for lunar lander with 1000000 timesteps training

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 246.18 +/- 24.25
+      value: 268.01 +/- 19.32
       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 0x7fe44e136dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe44e136e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe44e136ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe44e136f70>", "_build": "<function ActorCriticPolicy._build at 0x7fe44e13a040>", "forward": "<function ActorCriticPolicy.forward at 0x7fe44e13a0d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fe44e13a160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe44e13a1f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe44e13a280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe44e13a310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe44e13a3a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe44e13a430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe44e1b29f0>"}, "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": 262144, "_total_timesteps": 250000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673804379802212085, "learning_rate": 0.0003, "tensorboard_log": "./", "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": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 160, "n_steps": 1024, "gamma": 0.998, "gae_lambda": 0.99, "ent_coef": 0.005, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 5, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.15.79.1-microsoft-standard-WSL2-x86_64-with-glibc2.29 # 1 SMP Wed Nov 23 01:01:46 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.9.1+cu111", "GPU Enabled": "True", "Numpy": "1.23.4", "Gym": "0.21.0"}}
+{"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 0x7fe44e136dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe44e136e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe44e136ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe44e136f70>", "_build": "<function ActorCriticPolicy._build at 0x7fe44e13a040>", "forward": "<function ActorCriticPolicy.forward at 0x7fe44e13a0d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fe44e13a160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe44e13a1f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe44e13a280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe44e13a310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe44e13a3a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe44e13a430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe44e1b29f0>"}, "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": 262144, "_total_timesteps": 250000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673805653984059662, "learning_rate": 0.0003, "tensorboard_log": "./", "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": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 320, "n_steps": 1024, "gamma": 0.998, "gae_lambda": 0.99, "ent_coef": 0.005, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 5, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.15.79.1-microsoft-standard-WSL2-x86_64-with-glibc2.29 # 1 SMP Wed Nov 23 01:01:46 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.9.1+cu111", "GPU Enabled": "True", "Numpy": "1.23.4", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4f9c46b8b1fbe84cd75300525d5187e3cafedde2c66cc7165230934c58c5d213
-size 144329
+oid sha256:09ce6778f887533ba70a7dea203948b8c99d3cb6a74ae7fdb013dfe8d1f7e2d5
+size 144325

ppo-LunarLander-v2/data

@@ -48,7 +48,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1673804379802212085,
+    "start_time": 1673805653984059662,
     "learning_rate": 0.0003,
     "tensorboard_log": "./",
     "lr_schedule": {
@@ -57,7 +57,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAABqTmT3sSbi5QjoBOo+xOLdYoH461wIYuQAAgD8AAIA/INM4vtlJGj+Yqg88JJnevv/+8r2WtEE9AAAAAAAAAAAAtAM8UAe9P93liTv/wim+Uz5APdPnHj4AAAAAAAAAADOtYT04F+67xuYpPJZHjjzLHje9k0dvPQAAgD8AAIA/rRgOPp9m/z6zbN69ggPBvj+Phj1fKsk8AAAAAAAAAACmw7A+VW8QPwSPJr4ttf++82CHPsq7bb4AAAAAAAAAAOZfQD7YBIE9fjQdPYY4R76WdFg9YoKmPQAAAAAAAAAAMy5XPcN5Xrogr2o5QhdjNGI95DqtFIq4AACAPwAAgD8mxKA9EyQCP4HrJL6PZLa+yXCDvHpRC74AAAAAAAAAAJrDqj0UzKq6pTddNreXKTFPlYG5zU6DtQAAgD8AAIA/rZaAPlcKMb3+z8k9hV5yvP2jm76DMTC9AACAPwAAgD9KNZA+dEF7vZcKEDpZoCa5lKTYvo03V7kAAIA/AACAPyalGj4UmJa6Lva8uVOj+biRusY6QOX0OAAAgD8AAIA/zXi9u0MWfT0yTq29jstGvnox7b22h9Y6AAAAAAAAAABmCCq89iQGuvIMrD01iCMzAt8WuoEHSDMAAIA/AACAP5rNwbuqz3I+9gFQvYUujr5fV8u9o5/lvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -70,13 +70,13 @@
     "_current_progress_remaining": -0.04857599999999995,
     "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": 160,
+    "_n_updates": 320,
     "n_steps": 1024,
     "gamma": 0.998,
     "gae_lambda": 0.99,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:eb07b6cbe2254704b378e2ceec87d1c4b6bf5a8980ce33deb218e490d9e91131
-size 84829
+oid sha256:bd6f853519e301df9a85787ec2a394b00a9b28bd064af4826719297bd00fd484
+size 84893

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3525f19fbc8f2c83242d9d2b91edf44f3e33b8366e6fca46250abb56b4a7aa9d
+oid sha256:849f1d974f62e6a7077cbc0d384bedd1f9411623ec3eb1ee274bf237dbb8ad15
 size 43393

results.json

@@ -1 +1 @@
-{"mean_reward": 246.18017214131405, "std_reward": 24.245721541837344, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-15T17:50:59.204214"}
+{"mean_reward": 268.01271319905, "std_reward": 19.318346660955374, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-15T18:06:41.076720"}