model v3

PPO_spaceship.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:679397cb9c935b26d5a1d24880297f574f467541202f0c1ed96001e228dc0abb
-size 144050
+oid sha256:5e38bee1d9fd18b7c1fd849ca4edc2d53d4400ce01652306e7e945b4ca537f9e
+size 144044

PPO_spaceship/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 1507328,
+    "_total_timesteps": 1500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1652017032.7594266,
+    "start_time": 1652020678.05059,
     "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": -0.004885333333333408,
     "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": 310,
+    "_n_updates": 920,
     "n_steps": 1024,
-    "gamma": 0.9995,
-    "gae_lambda": 0.98,
-    "ent_coef": 0.01,
+    "gamma": 0.99,
+    "gae_lambda": 0.99,
+    "ent_coef": 0.015,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
     "batch_size": 256,
-    "n_epochs": 5,
+    "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

PPO_spaceship/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f4a8d492586e42e3f4d978a66c45a197d3e8c21fd65717fe5de7260631299122
+oid sha256:be324e3fed44348bde3d9e4a19cde1575d7e43b7f23bb72e4e66e1cc4842db98
 size 84829

PPO_spaceship/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ab9bc27d5bd68214cea674f081e21d0de93df151a124cdc8f030e2196bee2433
+oid sha256:62f4498c3d36ab8b76e3491ce2cde2eca7088c49ea68bdeb0e296a10c37eb92b
 size 43201

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 228.20 +/- 13.43
+      value: 257.05 +/- 37.79
       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 0x7fd03631d3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd03631d440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd03631d4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd03631d560>", "_build": "<function ActorCriticPolicy._build at 0x7fd03631d5f0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd03631d680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd03631d710>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd03631d7a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd03631d830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd03631d8c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd03631d950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd0363668d0>"}, "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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "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": 1652017032.7594266, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAObpWL3CF/A+Tu0/vAdrk76jyzU9Rq2qOwAAAAAAAAAANppvvqtwDz8dBE0+f4mGvniefz3DDBM9AAAAAAAAAAAAj5i8jw4vumhVhTpqf5k13osbOog2mrkAAIA/AACAP2YQDDyPwk26nroXOkR8lzS46Ta737gwuQAAgD8AAIA/4FGPPjvKOD+CBAa9e6hwvmdRsj3zg9C8AAAAAAAAAABNzEm9zO83PupbHz0ACSO+yG09PZMbED0AAAAAAAAAALNzi73XYy848nccuv6swTXfi6M5mg05OQAAgD8AAIA/TQpoPSSp3D4Q/lw7o78xvoXOfLxh/Ss9AAAAAAAAAABzUsu9ri+EutL+hjxef4s29ubpOqhXfzUAAIA/AACAP8ANLj7WH4g/Z+EaPpI5Ub5kN/M96JyBvAAAAAAAAAAA5hGUPex57rk+4ku75vgRNTi2bzpI23A6AACAPwAAgD99YaM+msM3PxLJvDweYZW+1gkQPgZ7070AAAAAAAAAALNwAD17ppC6Rndru0BT4LZXUIE61j6IOgAAgD8AAIA/AMB9u8ORKLpCCNe7N+GdN0MQlrsyrAG3AACAPwAAgD/A0LM9rv+6OVrMfTxNO188P4Omur1mdzwAAAAAAAAAAIDKaL2P/gi6jnJQutXnm7VxzLO66Fh1OQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": 310, "n_steps": 1024, "gamma": 0.9995, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 256, "n_epochs": 5, "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": "0.17.3"}}
+{"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 0x7fd03631d3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd03631d440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd03631d4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd03631d560>", "_build": "<function ActorCriticPolicy._build at 0x7fd03631d5f0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd03631d680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd03631d710>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd03631d7a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd03631d830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd03631d8c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd03631d950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd0363668d0>"}, "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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "n": 4, "shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652020678.05059, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 920, "n_steps": 1024, "gamma": 0.99, "gae_lambda": 0.99, "ent_coef": 0.015, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 256, "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": "0.17.3"}}

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bece6eef7c6125852cf7377c72604a31c7cec1a45a5b8269da24f315c41f9eef
-size 259080
+oid sha256:ef23f0843e843ddf8583368a670070bec4b1f07d529bf7232ab4840f5ec99d5b
+size 196182

results.json

@@ -1 +1 @@
-{"mean_reward": 228.20190668046348, "std_reward": 13.434688510300859, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-08T14:09:11.242816"}
+{"mean_reward": 257.0494906093583, "std_reward": 37.78933695789724, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-08T15:15:05.864969"}