Upload PPO LunarLander-v2 trained agent

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 223.47 +/- 66.53
+      value: 289.18 +/- 14.61
       name: mean_reward
     task:
       type: reinforcement-learning

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 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 0x7fac6ed72cb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fac6ed72d40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fac6ed72dd0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fac6ed72e60>", "_build": "<function ActorCriticPolicy._build at 0x7fac6ed72ef0>", "forward": "<function ActorCriticPolicy.forward at 0x7fac6ed72f80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fac6ed75050>", "_predict": "<function ActorCriticPolicy._predict at 0x7fac6ed750e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fac6ed75170>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fac6ed75200>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fac6ed75290>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fac6ed42780>"}, "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": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652010906.0363133, "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": -0.04857599999999995, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "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 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 0x7fac6ed72cb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fac6ed72d40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fac6ed72dd0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fac6ed72e60>", "_build": "<function ActorCriticPolicy._build at 0x7fac6ed72ef0>", "forward": "<function ActorCriticPolicy.forward at 0x7fac6ed72f80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fac6ed75050>", "_predict": "<function ActorCriticPolicy._predict at 0x7fac6ed750e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fac6ed75170>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fac6ed75200>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fac6ed75290>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fac6ed42780>"}, "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": 1652012973.0232725, "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": 470, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cc0a123ad2f0e2462ad8e39d8662c0de91a63dce6e054893a4034ca8ac0309c5
-size 144106
+oid sha256:6647ff96d2748d092f10d212881c2f43e6544520c8dd63c9f5bc59ef96671fbf
+size 143981

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 524288,
-    "_total_timesteps": 500000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1652010906.0363133,
+    "start_time": 1652012973.0232725,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,16 +66,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.04857599999999995,
+    "_current_progress_remaining": -0.015808000000000044,
     "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": 470,
     "n_steps": 2048,
     "gamma": 0.99,
     "gae_lambda": 0.95,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5e5c9590688c6fd217a361f089ca54a420328c3de0ff34b4c3aad93b62630bf6
+oid sha256:957c72eeb4362ff20144f55302ab780e5f17a8026f6006039e707d08e7661ad1
 size 84893

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:81e059d2ab63ae145dd26817ff148eaae4adab4e7dffe8c74b48801079f7e6ac
+oid sha256:af4a2124a6a47be50c0d2c0487845d0e6d9f0ef7dc7c8a0002524a17082dd7d0
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:74980e87ea3e4668ddceb6b5e54d893f73cadf2b7ebc772ca43520f34b08fb3e
-size 263937
+oid sha256:79faa68de9176cff78acb82eb630376654da92f1ca0730df0cc5fb221248d35f
+size 194931

results.json

@@ -1 +1 @@
-{"mean_reward": 223.46873653311414, "std_reward": 66.52826253817683, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-08T12:20:42.712445"}
+{"mean_reward": 289.1764808062777, "std_reward": 14.608635577517603, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-08T13:00:13.761233"}