2m frames

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 280.04 +/- 18.85
+      value: 257.11 +/- 52.40
       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 0x7f7881f0a3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7881f0a440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7881f0a4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7881f0a560>", "_build": "<function ActorCriticPolicy._build at 0x7f7881f0a5f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f7881f0a680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7881f0a710>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7881f0a7a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7881f0a830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7881f0a8c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7881f0a950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7881f49cf0>"}, "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": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651873191.0180867, "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": -0.007616000000000067, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 492, "n_steps": 1024, "gamma": 0.99, "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 0x7f7881f0a3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7881f0a440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7881f0a4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7881f0a560>", "_build": "<function ActorCriticPolicy._build at 0x7f7881f0a5f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f7881f0a680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7881f0a710>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7881f0a7a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7881f0a830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7881f0a8c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7881f0a950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7881f49cf0>"}, "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:": "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", "n": 4, "_shape": [], "dtype": "int64", "_np_random": "RandomState(MT19937)"}, "n_envs": 1, "num_timesteps": 4000768, "_total_timesteps": 4000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651878502.2962997, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAACa00r1BixI/4tkEPpJE0b5z1Cw9bs77uwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00019199999999996997, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 15628, "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"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ee02697c9acd5945acb4e1dfb6057f9aa22bc0d1b960bbc463046598e43614a0
-size 144009
+oid sha256:edc3f952ec08b90e0ea07da50ec3df9298114cb1fa9087004aacb57990752358
+size 147007

ppo-LunarLander-v2/data

@@ -35,19 +35,19 @@
     },
     "action_space": {
         ":type:": "<class 'gym.spaces.discrete.Discrete'>",
-        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        ":serialized:": "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",
         "n": 4,
         "_shape": [],
         "dtype": "int64",
-        "_np_random": null
+        "_np_random": "RandomState(MT19937)"
     },
-    "n_envs": 16,
-    "num_timesteps": 2015232,
-    "_total_timesteps": 2000000,
+    "n_envs": 1,
+    "num_timesteps": 4000768,
+    "_total_timesteps": 4000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651873191.0180867,
+    "start_time": 1651878502.2962997,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,28 +56,28 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAACa00r1BixI/4tkEPpJE0b5z1Cw9bs77uwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.007616000000000067,
+    "_current_progress_remaining": -0.00019199999999996997,
     "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": 492,
+    "_n_updates": 15628,
     "n_steps": 1024,
-    "gamma": 0.99,
+    "gamma": 0.999,
     "gae_lambda": 0.98,
     "ent_coef": 0.01,
     "vf_coef": 0.5,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9ec1efb95614a06c431b1fe046f3e18f6747ad906fd52674974ba49ffd3a8a50
+oid sha256:81972d417b9c1052305b796ca5b07913863f56b3b0508cca4acc9c4d428ac796
 size 84893

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3dfd6d5c5e81ff0fe65ff2a4322dd0837f5abce42e2e9140f4477d5ffab5ac98
+oid sha256:70d2428eab2881e5167f69c39fc0a9e4bbbab1b3ca1428fcff8a32a565ad98da
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d870f480eb392810855b269cbf09fe10434e4d8ac331a0a60ff41988839171ac
-size 217069
+oid sha256:3574d2162d726fe2fc7c0dbe4051272f277773b17ee28c95415465e91a9070bc
+size 193125

results.json

@@ -1 +1 @@
-{"mean_reward": 280.0433239325761, "std_reward": 18.847070735785138, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T22:20:33.984304"}
+{"mean_reward": 257.10954695080756, "std_reward": 52.397967623158976, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-07T01:13:27.379793"}