Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -4.16 +/- 0.91
+      value: -1.21 +/- 0.45
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8b4e4f4d9b0c1e7fc7a2e81f42326f5257655b9962571f541b924481858ef1d4
-size 108075
+oid sha256:136724d1bda49e8325383088287af0734057524b852c4d972049a046dbdde733
+size 109548

a2c-PandaReachDense-v2/data

@@ -11,7 +11,9 @@
     "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,
@@ -24,19 +26,19 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1685535192148202534,
-    "learning_rate": 0.0007,
+    "start_time": 1685542118913965620,
+    "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": "[[ 0.4106455  -0.04959986  0.5725732 ]\n [ 0.4106455  -0.04959986  0.5725732 ]\n [ 0.4106455  -0.04959986  0.5725732 ]\n [ 0.4106455  -0.04959986  0.5725732 ]]",
-        "desired_goal": "[[ 0.3243237  -1.222277   -1.115069  ]\n [-0.1062357  -0.7889387   0.0516072 ]\n [-1.2523463   0.29410112 -1.5231774 ]\n [-0.40539506 -0.18179023  0.13882479]]",
-        "observation": "[[ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]\n [ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]\n [ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]\n [ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[0.40383893 0.00789692 0.54762524]\n [0.40383893 0.00789692 0.54762524]\n [0.40383893 0.00789692 0.54762524]\n [0.40383893 0.00789692 0.54762524]]",
+        "desired_goal": "[[ 1.46456    -0.7200417   0.24960318]\n [ 1.3520172   0.7300927   0.4435776 ]\n [-1.4114617  -0.1858078   0.18697843]\n [-1.26352    -1.3634269  -0.6626883 ]]",
+        "observation": "[[0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]\n [0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]\n [0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]\n [0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -44,30 +46,30 @@
     },
     "_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": "[[ 0.01280754  0.08031278  0.06147534]\n [ 0.0999645   0.09327439  0.06398251]\n [-0.08583549  0.1454737   0.2687265 ]\n [-0.02796583 -0.08269761  0.2123703 ]]",
+        "desired_goal": "[[ 0.07036976 -0.00075201  0.23285641]\n [ 0.03546504 -0.0561871   0.2435151 ]\n [-0.07559567 -0.10416614  0.06387654]\n [ 0.08226043  0.02817935  0.21344522]]",
         "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,
     "_stats_window_size": 100,
     "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,
     "observation_space": {

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ead89db29b32751d301c847cbfd740482b8ef111a7746b9717c80bb4763e0fc7
-size 44734
+oid sha256:acd54a65459f988c8a8b60d766cf29c35ffb84fa78c2d5c50d967fd41679a249
+size 45438

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dfd2532e671e53389956cf522d5a716ec617b2080f808cf63f1287caaea682fb
-size 46014
+oid sha256:fb02e463abedb307a45849af8c62729df35a0ce6e18bb0a8f501dd24a0caeac3
+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 0x7fec0ca2a170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fec0ca18200>"}, "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}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685535192148202534, "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": "[[ 0.4106455  -0.04959986  0.5725732 ]\n [ 0.4106455  -0.04959986  0.5725732 ]\n [ 0.4106455  -0.04959986  0.5725732 ]\n [ 0.4106455  -0.04959986  0.5725732 ]]", "desired_goal": "[[ 0.3243237  -1.222277   -1.115069  ]\n [-0.1062357  -0.7889387   0.0516072 ]\n [-1.2523463   0.29410112 -1.5231774 ]\n [-0.40539506 -0.18179023  0.13882479]]", "observation": "[[ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]\n [ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]\n [ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]\n [ 0.4106455  -0.04959986  0.5725732  -0.0029278  -0.01022676  0.01397552]]"}, "_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": "[[ 0.01280754  0.08031278  0.06147534]\n [ 0.0999645   0.09327439  0.06398251]\n [-0.08583549  0.1454737   0.2687265 ]\n [-0.02796583 -0.08269761  0.2123703 ]]", "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, "_stats_window_size": 100, "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, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "gAWVWAMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZSMAUOUdJRSlIwEaGlnaJRoHiiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBZLA4WUaCF0lFKUjA1ib3VuZGVkX2JlbG93lGgeKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIXSUUpSMDWJvdW5kZWRfYWJvdmWUaB4olgMAAAAAAAAAAQEBlGgtSwOFlGghdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBZoGUsDhZRoG2geKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoIXSUUpRoJGgeKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFksDhZRoIXSUUpRoKWgeKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoM2geKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoOE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBlLBoWUaBtoHiiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLBoWUaCF0lFKUaCRoHiiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBZLBoWUaCF0lFKUaCloHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDNoHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDhOdWJ1aBlOaBBOaDhOdWIu", "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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "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 0x7fec0ca2a170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fec0ca18200>"}, "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}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685542118913965620, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuCQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9PdRBNVR1phZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[0.40383893 0.00789692 0.54762524]\n [0.40383893 0.00789692 0.54762524]\n [0.40383893 0.00789692 0.54762524]\n [0.40383893 0.00789692 0.54762524]]", "desired_goal": "[[ 1.46456    -0.7200417   0.24960318]\n [ 1.3520172   0.7300927   0.4435776 ]\n [-1.4114617  -0.1858078   0.18697843]\n [-1.26352    -1.3634269  -0.6626883 ]]", "observation": "[[0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]\n [0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]\n [0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]\n [0.40383893 0.00789692 0.54762524 0.07006849 0.00152672 0.06108306]]"}, "_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": "[[ 0.07036976 -0.00075201  0.23285641]\n [ 0.03546504 -0.0561871   0.2435151 ]\n [-0.07559567 -0.10416614  0.06387654]\n [ 0.08226043  0.02817935  0.21344522]]", "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, "_stats_window_size": 100, "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, "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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -4.159459488000721, "std_reward": 0.9113278944707984, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-31T13:59:22.297991"}
+{"mean_reward": -1.2117667043581606, "std_reward": 0.4514587205787547, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-31T15:15:58.822925"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9d756a2710624c6533688bc7e80bc4c8f3ea053e004b14422db3c7cc2a141bf2
+oid sha256:1e63f92c82682f2c0a89ca0dc1f59797bf60b2a127e0b7dbad12c07eb1ac0313
 size 2387