Upload ppo-LunarLander-v2 model with longer training session

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 94.98 +/- 95.30
+      value: 272.55 +/- 14.41
       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 0x7fcc884155f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcc88415680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcc88415710>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcc884157a0>", "_build": "<function ActorCriticPolicy._build at 0x7fcc88415830>", "forward": "<function ActorCriticPolicy.forward at 0x7fcc884158c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcc88415950>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcc884159e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcc88415a70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcc88415b00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcc88415b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcc883e9300>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651710920.0202937, "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": 124, "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, "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 0x7fcc884155f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcc88415680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcc88415710>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcc884157a0>", "_build": "<function ActorCriticPolicy._build at 0x7fcc88415830>", "forward": "<function ActorCriticPolicy.forward at 0x7fcc884158c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcc88415950>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcc884159e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcc88415a70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcc88415b00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcc88415b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcc883e9300>"}, "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": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651713102.009513, "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": 620, "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 sha256:055bf8b0e73db9525971fb065a3aac393588be327d40d1d9b21a7dceb75c3ebe
-size 144044
+oid sha256:a20b2210ab622ceffa08799b884a8db9b99c631d5da623220c153e4cca446bb9
+size 143984

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 2031616,
+    "_total_timesteps": 2000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651710920.0202937,
+    "start_time": 1651713102.009513,
     "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'>",
@@ -69,21 +69,21 @@
     "_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": 124,
-    "n_steps": 1024,
-    "gamma": 0.999,
-    "gae_lambda": 0.98,
-    "ent_coef": 0.01,
+    "_n_updates": 620,
+    "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": 4,
+    "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cc2a296ded231e600b66cd500b11d75e0ebebecb2de019e5d8de9498ff5eb4d5
-size 84829
+oid sha256:faa96ad6f76a3d4bd9b5c19510473510439456324e1e4f344cc272f7461b0d79
+size 84893

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cb9523961a4ca2d359de01d310704a961f5ba6e3536c5c89d6b680c436711b11
+oid sha256:de80429d18b4a24195680d0153fe1f46adefd94af1972b4e55331f6756a61786
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0ef097a8757a38d7f998f49cce7cc8190fb7fd8f69cbf392476912de3edc4203
-size 268884
+oid sha256:1c43f31e540bab36f3469d5b6c7a9d3da5faa40a0625ce25556ee0e8afcb9eae
+size 174802

results.json

@@ -1 +1 @@
-{"mean_reward": 94.9844215480658, "std_reward": 95.29956269203586, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T01:09:20.324537"}
+{"mean_reward": 272.5542841409009, "std_reward": 14.414232444113454, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T02:09:32.220919"}