Upload model to Hugging Face

PPO-mid-goal.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0b8e52239404b04a2ea3d1ba2ce8f0079ea09360cb5f87610f7ac1a80692c5f2
-size 150416
+oid sha256:8f881df8f6fcaf5b768d81e150a1ef0cf2520c9ce96c5995ea19a69289ed1dd4
+size 150400

PPO-mid-goal/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 0x7efce7bf5240>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efce7bf52d0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efce7bf5360>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efce7bf53f0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7efce7bf5480>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7efce7bf5510>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efce7bf55a0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efce7bf5630>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7efce7bf56c0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efce7bf5750>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efce7bf57e0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efce7bf5870>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7fd0332f1240>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd0332f12d0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd0332f1360>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd0332f13f0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fd0332f1480>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fd0332f1510>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd0332f15a0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd0332f1630>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fd0332f16c0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd0332f1750>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd0332f17e0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd0332f1870>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7efce7be1e00>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fd0332ddd40>"
     },
     "verbose": true,
     "policy_kwargs": {},
@@ -48,7 +48,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1681944438387488333,
+    "start_time": 1681945184113270346,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -57,7 +57,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVFQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJagAAAAAAAAACvKIEM2a1M/cby7QgAAyEIAAMhCAADIQnxriUIAAMhCAADIQv/9tELYz1ZDLLjzvgAAyEIAAMhCbgUUQrYsPkJCysdCAADIQj9HhEIpmPRBCsQUQ26GET8fiqJCAADIQgAAyELI2k9CkPaPQgAAyEIAAMhCQsGrQs4kJ0P9gKM+AADIQgAAyEIAAMhCZAK2QgAAyEIAAMhCAADIQgAAyEKUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLCoaUjAFDlHSUUpQu"
+        ":serialized:": "gAWVFQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJagAAAAAAAAAPDH20KvTye/ACpYQnT+LUIGjEZCAADIQgAAyEIAAMhCAADIQgAAyEJa0NtCE/nqvwAAyEJ1fpxCbVQ9QvCLLkKtqYRCAADIQkmJsUIAAMhCGZPUQnrX8b8AAMhCQ/d8Quk3NkKVTS5CJlOfQgAAyEISiMVCAADIQuXF7EL/H50//nEuQgAAyEIAAMhCLRquQgAAyEIAAMhChoY6Qtn6BUKUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLCoaUjAFDlHSUUpQu"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -70,13 +70,13 @@
     "_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'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 750,
+    "_n_updates": 880,
     "n_steps": 2048,
     "gamma": 0.99,
     "gae_lambda": 0.5,

PPO-mid-goal/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4c585fd4c74f33ba1955b6e1120f00e082086a24589e506e7f0ed14f0dd91a0a
+oid sha256:3a87d423dce8ae6af5093269fc11758be5bcaa19f43cb3ef39583a9c09871e43
 size 90105

PPO-mid-goal/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:29f67a2479714401ed6a85c1c9caa1bd6418db0864706440043b427c41bcd08f
+oid sha256:562def091f9a07191a712d2d50f0dbdbebc0735a7e91716f1ced1787486b47d4
 size 44417

README.md

@@ -16,7 +16,7 @@ model-index:
       type: RoombaAToB-mid-goal
     metrics:
     - type: mean_reward
-      value: 125.70 +/- 0.00
+      value: 595.49 +/- 0.00
       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 0x7efce7bf5240>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efce7bf52d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efce7bf5360>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efce7bf53f0>", "_build": "<function ActorCriticPolicy._build at 0x7efce7bf5480>", "forward": "<function ActorCriticPolicy.forward at 0x7efce7bf5510>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efce7bf55a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efce7bf5630>", "_predict": "<function ActorCriticPolicy._predict at 0x7efce7bf56c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efce7bf5750>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efce7bf57e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efce7bf5870>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efce7be1e00>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [10], "low": "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]", "high": "[5.2000000e+05 3.1415927e+00 1.0000000e+02 1.0000000e+02 1.0000000e+02\n 1.0000000e+02 1.0000000e+02 1.0000000e+02 1.0000000e+02 1.0000000e+02]", "bounded_below": "[ True  True  True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True  True  True]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1681944438387488333, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVFQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJagAAAAAAAAACvKIEM2a1M/cby7QgAAyEIAAMhCAADIQnxriUIAAMhCAADIQv/9tELYz1ZDLLjzvgAAyEIAAMhCbgUUQrYsPkJCysdCAADIQj9HhEIpmPRBCsQUQ26GET8fiqJCAADIQgAAyELI2k9CkPaPQgAAyEIAAMhCQsGrQs4kJ0P9gKM+AADIQgAAyEIAAMhCZAK2QgAAyEIAAMhCAADIQgAAyEKUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLCoaUjAFDlHSUUpQu"}, "_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": 750, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.5, "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-5.19.0-35-generic-x86_64-with-glibc2.35 # 36~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Feb 17 15:17:25 UTC 2", "Python": "3.10.9", "Stable-Baselines3": "1.7.0", "PyTorch": "2.0.0", "GPU Enabled": "True", "Numpy": "1.23.5", "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 0x7fd0332f1240>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd0332f12d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd0332f1360>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd0332f13f0>", "_build": "<function ActorCriticPolicy._build at 0x7fd0332f1480>", "forward": "<function ActorCriticPolicy.forward at 0x7fd0332f1510>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd0332f15a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd0332f1630>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd0332f16c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd0332f1750>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd0332f17e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd0332f1870>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd0332ddd40>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [10], "low": "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]", "high": "[5.2000000e+05 3.1415927e+00 1.0000000e+02 1.0000000e+02 1.0000000e+02\n 1.0000000e+02 1.0000000e+02 1.0000000e+02 1.0000000e+02 1.0000000e+02]", "bounded_below": "[ True  True  True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True  True  True]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1681945184113270346, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVFQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJagAAAAAAAAAPDH20KvTye/ACpYQnT+LUIGjEZCAADIQgAAyEIAAMhCAADIQgAAyEJa0NtCE/nqvwAAyEJ1fpxCbVQ9QvCLLkKtqYRCAADIQkmJsUIAAMhCGZPUQnrX8b8AAMhCQ/d8Quk3NkKVTS5CJlOfQgAAyEISiMVCAADIQuXF7EL/H50//nEuQgAAyEIAAMhCLRquQgAAyEIAAMhChoY6Qtn6BUKUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLCoaUjAFDlHSUUpQu"}, "_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": 880, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.5, "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-5.19.0-35-generic-x86_64-with-glibc2.35 # 36~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Feb 17 15:17:25 UTC 2", "Python": "3.10.9", "Stable-Baselines3": "1.7.0", "PyTorch": "2.0.0", "GPU Enabled": "True", "Numpy": "1.23.5", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": 125.7033746233324, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-19T15:54:47.726224"}
+{"mean_reward": 595.489271303274, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-19T16:07:18.229311"}