Upload trainder agent

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 122.75 +/- 118.20
+      value: 283.00 +/- 18.04
       name: mean_reward
     task:
       type: reinforcement-learning

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f93a336c440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f93a336c4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f93a336c560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f93a336c5f0>", "_build": "<function ActorCriticPolicy._build at 0x7f93a336c680>", "forward": "<function ActorCriticPolicy.forward at 0x7f93a336c710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f93a336c7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f93a336c830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f93a336c8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f93a336c950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f93a336c9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f93a333f240>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1655659846.4136107, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_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:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f93a336c440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f93a336c4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f93a336c560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f93a336c5f0>", "_build": "<function ActorCriticPolicy._build at 0x7f93a336c680>", "forward": "<function ActorCriticPolicy.forward at 0x7f93a336c710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f93a336c7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f93a336c830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f93a336c8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f93a336c950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f93a336c9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f93a333f240>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1655661437.783476, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 2448, "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": 8, "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.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a15f796f9d6e7e20ab3c866b9b216725a24d2e8af4b6233cdecb497deffa91b1
-size 144144
+oid sha256:54b66feeaf09b0407e953ecce4f5ced6b5126b1515c4371b299095171a8b8b19
+size 144090

ppo_lunarlander/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 5013504,
+    "_total_timesteps": 5000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1655659846.4136107,
+    "start_time": 1655661437.783476,
     "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'>",
@@ -66,24 +66,24 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.0027007999999999477,
     "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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
+    "_n_updates": 2448,
     "n_steps": 1024,
-    "gamma": 0.999,
+    "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,
+    "n_epochs": 8,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

ppo_lunarlander/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:91327aa21dac038408040e78ab20565c8a06867f22629d40f3bdf05361af445d
-size 84829
+oid sha256:87233583960ee368422eb6a96d380a19c0cfe8ec680977ea588c3b01575d46a0
+size 84893

ppo_lunarlander/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2750802b4799ad7caeb2570968c0c3d4a21019aef47320bcd55e37f57508a851
+oid sha256:0a593ece2ea13ece151bf043d600ef13d5178777345afb6b78a48272d2afb3bc
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:34f994aba55446a4594bdd1661bde7dc5972a1ff8d60088988f13a1aa369e37f
-size 244411
+oid sha256:f6f9a885bbd6dadaa95e48d580cd25871b56b8b667e38338224c7a650a36ee4d
+size 191298

results.json

@@ -1 +1 @@
-{"mean_reward": 122.75299000325978, "std_reward": 118.19754402577253, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-19T17:52:50.225002"}
+{"mean_reward": 283.00436291307625, "std_reward": 18.04389998556615, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-19T19:18:33.992523"}