Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -4.05 +/- 1.61
+      value: -1.07 +/- 0.47
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:30aabfcbcf0ccca148f75821c2f5fb4b05de988713814a60bdaf2de6a81ce58d
-size 108071
+oid sha256:2751e4c40bb0d1a1efeb8468f19361c6c92cc56569346ec672346539f68ec952
+size 109616

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 0x7fbfaf323820>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f78891c4af0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7fbfaf31cb40>"
+        "_abc_impl": "<_abc_data object at 0x7f78891bf8a0>"
     },
     "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": 1677670967074823263,
-    "learning_rate": 0.0007,
+    "start_time": 1677675434914800736,
+    "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": "[[0.3863665  0.01443496 0.60721356]\n [0.3863665  0.01443496 0.60721356]\n [0.3863665  0.01443496 0.60721356]\n [0.3863665  0.01443496 0.60721356]]",
-        "desired_goal": "[[-1.1875851  -1.533938    0.7677741 ]\n [-1.6750829   0.27454984  0.7664905 ]\n [-1.3631757  -0.601284    0.09047166]\n [ 0.2212336  -0.1818438   0.8912549 ]]",
-        "observation": "[[3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]\n [3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]\n [3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]\n [3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.49076927 -0.00568089  0.56388193]\n [ 0.49076927 -0.00568089  0.56388193]\n [ 0.49076927 -0.00568089  0.56388193]\n [ 0.49076927 -0.00568089  0.56388193]]",
+        "desired_goal": "[[ 0.6956504   0.6810622  -1.1516253 ]\n [-1.6312896   1.252799    1.5086002 ]\n [ 1.0586886  -1.6890948  -0.9885415 ]\n [ 0.0041811  -1.6913228  -0.79021895]]",
+        "observation": "[[ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]\n [ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]\n [ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]\n [ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,29 +68,29 @@
     },
     "_last_original_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
+        ":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": "[[ 0.09919517 -0.07625675  0.25416413]\n [ 0.08735611 -0.11400037  0.24924636]\n [ 0.13916664  0.08703632  0.02372191]\n [-0.1412612  -0.08825315  0.02368097]]",
+        "desired_goal": "[[ 0.00421539  0.11474367  0.00206006]\n [-0.14791337 -0.14998764  0.04796239]\n [ 0.11582205 -0.10189211  0.066105  ]\n [ 0.00203072  0.11245468  0.0697476 ]]",
         "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": 50000,
-    "n_steps": 5,
+    "_n_updates": 31250,
+    "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 sha256:263dda3deea5aea43ddc941882b038a1f4503e0990456407c8e5d435509e5d93
-size 44734
+oid sha256:2742e08390b26ce2be1fc44b3b8a05bd98596bfc9144a23c4581c93b852ac677
+size 45438

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fc5cddbd417c5a46ee5800984304facb7d184e7a1f713070e10df9e4a9d7bd6c
-size 46014
+oid sha256:37fa4f12f42acf3e1fa3314f0d980e535f07b890e6977ba8ed8d978e1cd75038
+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 0x7fbfaf323820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fbfaf31cb40>"}, "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": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677670967074823263, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA1NHFPp6AbDxZchs/1NHFPp6AbDxZchs/1NHFPp6AbDxZchs/1NHFPp6AbDxZchs/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAygKYvxVYxL/YjEQ/HmnWv8yRjD65OEQ/i3yuv8DtGb80Sbk9EItiPkM1Or5IKWQ/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADU0cU+noBsPFlyGz84pIA88sMXOmLDTDzU0cU+noBsPFlyGz84pIA88sMXOmLDTDzU0cU+noBsPFlyGz84pIA88sMXOmLDTDzU0cU+noBsPFlyGz84pIA88sMXOmLDTDyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.3863665  0.01443496 0.60721356]\n [0.3863665  0.01443496 0.60721356]\n [0.3863665  0.01443496 0.60721356]\n [0.3863665  0.01443496 0.60721356]]", "desired_goal": "[[-1.1875851  -1.533938    0.7677741 ]\n [-1.6750829   0.27454984  0.7664905 ]\n [-1.3631757  -0.601284    0.09047166]\n [ 0.2212336  -0.1818438   0.8912549 ]]", "observation": "[[3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]\n [3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]\n [3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]\n [3.8636649e-01 1.4434962e-02 6.0721356e-01 1.5703306e-02 5.7893910e-04\n  1.2497755e-02]]"}, "_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": "[[ 0.09919517 -0.07625675  0.25416413]\n [ 0.08735611 -0.11400037  0.24924636]\n [ 0.13916664  0.08703632  0.02372191]\n [-0.1412612  -0.08825315  0.02368097]]", "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": 50000, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "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 0x7f78891c4af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f78891bf8a0>"}, "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": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677675434914800736, "learning_rate": 0.00096, "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": "[[ 0.49076927 -0.00568089  0.56388193]\n [ 0.49076927 -0.00568089  0.56388193]\n [ 0.49076927 -0.00568089  0.56388193]\n [ 0.49076927 -0.00568089  0.56388193]]", "desired_goal": "[[ 0.6956504   0.6810622  -1.1516253 ]\n [-1.6312896   1.252799    1.5086002 ]\n [ 1.0586886  -1.6890948  -0.9885415 ]\n [ 0.0041811  -1.6913228  -0.79021895]]", "observation": "[[ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]\n [ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]\n [ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]\n [ 4.9076927e-01 -5.6808894e-03  5.6388193e-01  6.3979730e-02\n   2.0512896e-05  5.4269284e-02]]"}, "_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": "[[ 0.00421539  0.11474367  0.00206006]\n [-0.14791337 -0.14998764  0.04796239]\n [ 0.11582205 -0.10189211  0.066105  ]\n [ 0.00203072  0.11245468  0.0697476 ]]", "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": 31250, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "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": -4.046263332292438, "std_reward": 1.606793883898247, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-01T12:43:54.378440"}
+{"mean_reward": -1.071541674155742, "std_reward": 0.4691001456739032, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-01T13:52:12.968016"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1e012031c769722e0fd18e24a0c940d3be78338c9a6d51d13ed549de10e45d77
+oid sha256:7b2c21d84b307e4063ea7822d6e559921641ad7a2dd02acd642d8346dbbbc722
 size 3056