Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -3.15 +/- 1.38
+      value: -0.93 +/- 0.38
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:804d5184a6e44a8a1b15e4e700e8a96c44c4fc5fd2859c42bb2dc89fa9b60173
-size 108101
+oid sha256:e106838f5ea97d12f5b47f0ebce53fa2034dc8dbb64419749d508830488538b1
+size 109501

a2c-PandaReachDense-v2/data

@@ -4,14 +4,16 @@
         ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
         "__module__": "stable_baselines3.common.policies",
         "__doc__": "\n    MultiInputActorClass 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 (Tuple)\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: Uses the CombinedExtractor\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 MultiInputActorCriticPolicy.__init__ at 0x7fd0618c45e0>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f48cc4c2820>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fd0618c3a80>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f48cc4c5340>"
     },
     "verbose": 1,
     "policy_kwargs": {
         ":type:": "<class 'dict'>",
-        ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
+        ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
+        "log_std_init": -2,
+        "ortho_init": false,
         "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
         "optimizer_kwargs": {
             "alpha": 0.99,
@@ -46,19 +48,19 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1679219297522440257,
-    "learning_rate": 0.0007,
+    "start_time": 1679309038780603738,
+    "learning_rate": 0.00096,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
-        "achieved_goal": "[[0.42451864 0.03905096 0.5904165 ]\n [0.42451864 0.03905096 0.5904165 ]\n [0.42451864 0.03905096 0.5904165 ]\n [0.42451864 0.03905096 0.5904165 ]]",
-        "desired_goal": "[[ 0.02883514  1.0596104   0.0778428 ]\n [-0.57467324  0.1492287   1.3550783 ]\n [-0.6933723  -0.21802299  0.12196586]\n [ 0.44219503  0.48272434  1.5411838 ]]",
-        "observation": "[[ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]\n [ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]\n [ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]\n [ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[0.42971832 0.00317847 0.57811147]\n [0.42971832 0.00317847 0.57811147]\n [0.42971832 0.00317847 0.57811147]\n [0.42971832 0.00317847 0.57811147]]",
+        "desired_goal": "[[ 1.2344797   0.93813556 -0.90681773]\n [-0.2860058  -1.1766536  -1.542987  ]\n [-1.0315566   0.27368394  1.3309685 ]\n [ 0.42359504  1.3696448  -1.396974  ]]",
+        "observation": "[[0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]\n [0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]\n [0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]\n [0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,29 +68,29 @@
     },
     "_last_original_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
+        ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAnuAUPHqLab0UrcE8S7kIPKQ0Cz7NHog+b2CpvYyRBr6zvFs+DiHMvcEaP73ZzMY9lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==",
         "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]",
-        "desired_goal": "[[ 0.09169816 -0.03808992  0.17549361]\n [ 0.03139735  0.0578013   0.27511477]\n [ 0.10148923 -0.05089486  0.27161872]\n [-0.05030368  0.09087985  0.1052366 ]]",
+        "desired_goal": "[[ 0.00908676 -0.05701778  0.0236421 ]\n [ 0.00834496  0.135943    0.26586   ]\n [-0.08270346 -0.13141459  0.21458702]\n [-0.09967242 -0.04665637  0.0970704 ]]",
         "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"
     },
     "_episode_num": 0,
-    "use_sde": false,
+    "use_sde": true,
     "sde_sample_freq": -1,
     "_current_progress_remaining": 0.0,
     "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": 100000,
-    "n_steps": 5,
+    "_n_updates": 62500,
+    "n_steps": 8,
     "gamma": 0.99,
-    "gae_lambda": 1.0,
+    "gae_lambda": 0.9,
     "ent_coef": 0.0,
-    "vf_coef": 0.5,
+    "vf_coef": 0.4,
     "max_grad_norm": 0.5,
     "normalize_advantage": false
 }

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:548b4cce072ad975cc435031b58f2722012b768b3cd59c192e36b089498f59ca
-size 44734
+oid sha256:e1146f82ed5ac22043a3afb0b069d4c65c1eb5e5919b0b9316076f98a7092f31
+size 45438

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6a695a6ce6717d6ae5799cd52b1787921595c62b7c1550179c1fad0bce055bbd
-size 46014
+oid sha256:d19714beba2e4a0554e149182dc6bec107cff3ab7f99e1222f36439fc6877617
+size 46718

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    MultiInputActorClass 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 (Tuple)\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: Uses the CombinedExtractor\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 MultiInputActorCriticPolicy.__init__ at 0x7fd0618c45e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd0618c3a80>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679219297522440257, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[0.42451864 0.03905096 0.5904165 ]\n [0.42451864 0.03905096 0.5904165 ]\n [0.42451864 0.03905096 0.5904165 ]\n [0.42451864 0.03905096 0.5904165 ]]", "desired_goal": "[[ 0.02883514  1.0596104   0.0778428 ]\n [-0.57467324  0.1492287   1.3550783 ]\n [-0.6933723  -0.21802299  0.12196586]\n [ 0.44219503  0.48272434  1.5411838 ]]", "observation": "[[ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]\n [ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]\n [ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]\n [ 4.2451864e-01  3.9050963e-02  5.9041649e-01 -1.5816113e-03\n  -1.1497317e-04  9.6825222e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]", "desired_goal": "[[ 0.09169816 -0.03808992  0.17549361]\n [ 0.03139735  0.0578013   0.27511477]\n [ 0.10148923 -0.05089486  0.27161872]\n [-0.05030368  0.09087985  0.1052366 ]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 100000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    MultiInputActorClass 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 (Tuple)\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: Uses the CombinedExtractor\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 MultiInputActorCriticPolicy.__init__ at 0x7f48cc4c2820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f48cc4c5340>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679309038780603738, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAACgTcPuNNUDsd/xM/CgTcPuNNUDsd/xM/CgTcPuNNUDsd/xM/CgTcPuNNUDsd/xM/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAbgOeP6cpcD81JWi/Wm+Svpaclr+ZgMW/DAqEv00gjD4tXao/c+HYPoVQrz8L0LK/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAAKBNw+401QOx3/Ez8H0Yw9APZlOuNoij0KBNw+401QOx3/Ez8H0Yw9APZlOuNoij0KBNw+401QOx3/Ez8H0Yw9APZlOuNoij0KBNw+401QOx3/Ez8H0Yw9APZlOuNoij2UaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.42971832 0.00317847 0.57811147]\n [0.42971832 0.00317847 0.57811147]\n [0.42971832 0.00317847 0.57811147]\n [0.42971832 0.00317847 0.57811147]]", "desired_goal": "[[ 1.2344797   0.93813556 -0.90681773]\n [-0.2860058  -1.1766536  -1.542987  ]\n [-1.0315566   0.27368394  1.3309685 ]\n [ 0.42359504  1.3696448  -1.396974  ]]", "observation": "[[0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]\n [0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]\n [0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]\n [0.42971832 0.00317847 0.57811147 0.06875806 0.00087723 0.06758287]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]", "desired_goal": "[[ 0.00908676 -0.05701778  0.0236421 ]\n [ 0.00834496  0.135943    0.26586   ]\n [-0.08270346 -0.13141459  0.21458702]\n [-0.09967242 -0.04665637  0.0970704 ]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -3.1520896846428514, "std_reward": 1.375176051759476, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-19T11:30:55.971952"}
+{"mean_reward": -0.9286860883701593, "std_reward": 0.3757227848575661, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-20T12:42:27.831268"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e406ccd82da716c6ae91f309afa8189413cca05e2817f631ce0e6dc7bf7629b0
+oid sha256:fcb629c55343082a608a513e634081af76637fb0f7492c4a9acfa6d112b73663
 size 3056