train 500k timestemps

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: -181.42 +/- 55.25
+      value: 208.85 +/- 76.36
       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 0x7fe8a3fb9a70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe8a3fb9b00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe8a3fb9b90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe8a3fb9c20>", "_build": "<function ActorCriticPolicy._build at 0x7fe8a3fb9cb0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe8a3fb9d40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe8a3fb9dd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe8a3fb9e60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe8a3fb9ef0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe8a3fb9f80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe8a3fbd050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe8a3ff9e10>"}, "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": 0, "_total_timesteps": 0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": null, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": null, "_last_episode_starts": null, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 1, "ep_info_buffer": null, "ep_success_buffer": null, "_n_updates": 0, "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 0x7fe8a3fb9a70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe8a3fb9b00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe8a3fb9b90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe8a3fb9c20>", "_build": "<function ActorCriticPolicy._build at 0x7fe8a3fb9cb0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe8a3fb9d40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe8a3fb9dd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe8a3fb9e60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe8a3fb9ef0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe8a3fb9f80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe8a3fbd050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe8a3ff9e10>"}, "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": 491520, "_total_timesteps": 480000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652105563.5177898, "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": -0.02400000000000002, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 150, "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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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_model1.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f055ad2a81d044b5d779c4a3ec402528bc627fd1d0d01dd416a10b37f59520e1
-size 52731
+oid sha256:708f270ce2b08c52deae520caa500f3813fee4771c99a112fe1cf42d5a0bed64
+size 144102

ppo_model1/data

@@ -42,28 +42,40 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 0,
-    "_total_timesteps": 0,
+    "num_timesteps": 491520,
+    "_total_timesteps": 480000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": null,
+    "start_time": 1652105563.5177898,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"
     },
-    "_last_obs": null,
-    "_last_episode_starts": null,
+    "_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": 1,
-    "ep_info_buffer": null,
-    "ep_success_buffer": null,
-    "_n_updates": 0,
+    "_current_progress_remaining": -0.02400000000000002,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 150,
     "n_steps": 2048,
     "gamma": 0.99,
     "gae_lambda": 0.95,

ppo_model1/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dab7f743c00d9fd8f6843d71d518a2be6a3427eb880347ab76205a81135ee5c8
-size 623
+oid sha256:bfc55cf6bb6071250cb95c91e07e78e8bf34dd27cd7d778d47378fecb46c5be0
+size 84893

ppo_model1/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d34f96efd922515829d736ba404a4cbc9f3950dc1e8d971ab545617597d6459c
+oid sha256:d1bf205f465db9c31d30457850ee828fdf8d8692a0e6795297ff4b9aac093021
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:141030158f2cb7f128f87626d175515ca3dec55f89437f3ee4e8877dd6383cc3
-size 150735
+oid sha256:400e00333231d6d56beeaa3e669751f1013ffcd5ced458775699b31d88d0d798
+size 251576

results.json

@@ -1 +1 @@
-{"mean_reward": -181.41948641879716, "std_reward": 55.25297608210953, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-09T14:11:35.520548"}
+{"mean_reward": 208.85274678132674, "std_reward": 76.35842162808157, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-09T14:29:43.684462"}