Upload model to Hugging Face

PPO-default.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8a0f9881317473aeaf9469242adc455024f0e92f01804d6460b1c4f7c8a70101
-size 136815
+oid sha256:7d2203e13fc24bc109b29b308da4abaaad109df05868affdfd1a228892c37f82
+size 137055

PPO-default/data

@@ -4,20 +4,20 @@
         ":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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f8c6b8253f0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8c6b825480>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8c6b825510>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8c6b8255a0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f8c6b825630>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f8c6b8256c0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8c6b825750>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8c6b8257e0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f8c6b825870>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8c6b825900>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8c6b825990>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8c6b825a20>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7fce9cf353f0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fce9cf35480>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fce9cf35510>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fce9cf355a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fce9cf35630>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fce9cf356c0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fce9cf35750>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fce9cf357e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fce9cf35870>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fce9cf35900>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fce9cf35990>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fce9cf35a20>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f8c6b821800>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fce9cf31ac0>"
     },
     "verbose": true,
     "policy_kwargs": {},
@@ -48,7 +48,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1675309250624664455,
+    "start_time": 1675309977804194538,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -57,7 +57,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVpQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYwAAAAAAAAAAAAgD8AAIA/AACAPwAAgD8AAIA/T4F/PwAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBEsDhpSMAUOUdJRSlC4="
+        ":serialized:": "gAWVpQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYwAAAAAAAAAAAAgD8AAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/AACAPwAAgD/AgC4/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBEsDhpSMAUOUdJRSlC4="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -70,7 +70,7 @@
     "_current_progress_remaining": -0.0649599999999999,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",

PPO-default/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a066fe2aac9566c4ef4edabdba9522698b1d9d4abe625bd2f8b0396c6f730969
+oid sha256:83adb306f04a300a456711aea47c048d28cd05b552ab06807d86127335303350
 size 82809

PPO-default/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4601ccd1f8fba2d8189b3ded94f1adf30986550df8be2055f82299b8e930c861
+oid sha256:11d16ade94e051591d7ba9804e0e6c5e6406848085d49be27079395bc24583e9
 size 40833

README.md

@@ -16,7 +16,7 @@ model-index:
       type: Roomba
     metrics:
     - type: mean_reward
-      value: 29.20 +/- 99.88
+      value: 215.78 +/- 264.27
       name: mean_reward
       verified: false
 ---

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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f8c6b8253f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8c6b825480>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8c6b825510>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8c6b8255a0>", "_build": "<function ActorCriticPolicy._build at 0x7f8c6b825630>", "forward": "<function ActorCriticPolicy.forward at 0x7f8c6b8256c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8c6b825750>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8c6b8257e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8c6b825870>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8c6b825900>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8c6b825990>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8c6b825a20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8c6b821800>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[0. 0. 0.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_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": 4, "num_timesteps": 106496, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675309250624664455, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVpQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYwAAAAAAAAAAAAgD8AAIA/AACAPwAAgD8AAIA/T4F/PwAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBEsDhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0649599999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 130, "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-5.15.0-58-generic-x86_64-with-glibc2.35 # 64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023", "Python": "3.10.9", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.24.1", "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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7fce9cf353f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fce9cf35480>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fce9cf35510>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fce9cf355a0>", "_build": "<function ActorCriticPolicy._build at 0x7fce9cf35630>", "forward": "<function ActorCriticPolicy.forward at 0x7fce9cf356c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fce9cf35750>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fce9cf357e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fce9cf35870>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fce9cf35900>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fce9cf35990>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fce9cf35a20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fce9cf31ac0>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[0. 0. 0.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_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": 4, "num_timesteps": 106496, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675309977804194538, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVpQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYwAAAAAAAAAAAAgD8AAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/AACAPwAAgD/AgC4/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBEsDhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0649599999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 130, "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-5.15.0-58-generic-x86_64-with-glibc2.35 # 64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023", "Python": "3.10.9", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.24.1", "Gym": "0.21.0"}}

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b697daee6e4bb2fd7c36491bec9363bd1c7bbab830e9dc7ca364748f71badec2
-size 1332749
+oid sha256:d6dc39492217ccba2032bc95a10e575f17c40a8499670c6fe2541bdf5850ee4f
+size 1311028

results.json

@@ -1 +1 @@
-{"mean_reward": 29.2, "std_reward": 99.8767240151578, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-01T19:42:59.241308"}
+{"mean_reward": 215.77794880000002, "std_reward": 264.2729361521969, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-01T19:55:04.121734"}