Hugging Face's logo

matheusgeda
/
a2c-PandaReachDense-v3

Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results
Model card Files Community
matheusgeda commited on
Commit
8fb9faf
•
1 Parent(s): 2c67939

Initial commit

Browse files
Files changed (9) hide show
  1. README.md +1 -1
  2. a2c-PandaReachDense-v3.zip +2 -2
  3. a2c-PandaReachDense-v3/data +11 -11
  4. a2c-PandaReachDense-v3/policy.optimizer.pth +1 -1
  5. a2c-PandaReachDense-v3/policy.pth +1 -1
  6. config.json +1 -1
  7. replay.mp4 +0 -0
  8. results.json +1 -1
  9. vec_normalize.pkl +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: PandaReachDense-v3
17
  metrics:
18
  - type: mean_reward
19
- value: -0.22 +/- 0.11
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v3
17
  metrics:
18
  - type: mean_reward
19
+ value: -0.21 +/- 0.12
20
  name: mean_reward
21
  verified: false
22
  ---
a2c-PandaReachDense-v3.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5405a2173cf50e2348d3f5f5a86aa77490911007e32fc1a0d513e9bacca7c8fe
3
- size 106829
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f11922e4b1ac169a6be51e8095fdbff8b1dda896a5c89ec122b9616afb4aad22
3
+ size 106832
a2c-PandaReachDense-v3/data CHANGED
@@ -19,20 +19,20 @@
19
  "weight_decay": 0
20
  }
21
  },
22
- "num_timesteps": 100000,
23
- "_total_timesteps": 100000,
24
  "_num_timesteps_at_start": 0,
25
  "seed": null,
26
  "action_noise": null,
27
- "start_time": 1697024267864724591,
28
  "learning_rate": 0.0007,
29
  "tensorboard_log": null,
30
  "_last_obs": {
31
  ":type:": "<class 'collections.OrderedDict'>",
32
- ":serialized:": "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",
33
- "achieved_goal": "[[-0.20093498 -0.18957357 0.09378213]\n [-0.8835499 0.19210936 -1.0430254 ]\n [ 0.02261676 0.02432236 0.32938737]\n [-0.5342337 0.6523512 -0.55964124]]",
34
- "desired_goal": "[[ 0.23513773 -1.1786981 -0.24170214]\n [-1.5322638 0.391578 -1.5018995 ]\n [ 0.10614126 -1.1672944 0.0847332 ]\n [-0.15690142 0.97975844 -1.2024734 ]]",
35
- "observation": "[[-0.20093498 -0.18957357 0.09378213 -1.2458042 -1.8696011 -0.82258666]\n [-0.8835499 0.19210936 -1.0430254 -1.9137871 -1.0158666 -1.1267449 ]\n [ 0.02261676 0.02432236 0.32938737 0.23782827 -0.00500925 0.17554484]\n [-0.5342337 0.6523512 -0.55964124 -1.1704416 1.1311779 -1.0844946 ]]"
36
  },
37
  "_last_episode_starts": {
38
  ":type:": "<class 'numpy.ndarray'>",
@@ -40,9 +40,9 @@
40
  },
41
  "_last_original_obs": {
42
  ":type:": "<class 'collections.OrderedDict'>",
43
- ":serialized:": "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",
44
  "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]]",
45
- "desired_goal": "[[ 0.10391861 0.12532616 0.19721194]\n [-0.03183095 0.06693086 0.03856337]\n [ 0.00167038 -0.10475341 0.08401383]\n [-0.02432316 0.131114 0.2993231 ]]",
46
  "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]]"
47
  },
48
  "_episode_num": 0,
@@ -52,13 +52,13 @@
52
  "_stats_window_size": 100,
53
  "ep_info_buffer": {
54
  ":type:": "<class 'collections.deque'>",
55
- ":serialized:": "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"
56
  },
57
  "ep_success_buffer": {
58
  ":type:": "<class 'collections.deque'>",
59
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
60
  },
61
- "_n_updates": 5000,
62
  "n_steps": 5,
63
  "gamma": 0.99,
64
  "gae_lambda": 1.0,
 
19
  "weight_decay": 0
20
  }
21
  },
22
+ "num_timesteps": 1000000,
23
+ "_total_timesteps": 1000000,
24
  "_num_timesteps_at_start": 0,
25
  "seed": null,
26
  "action_noise": null,
27
+ "start_time": 1697024770975973009,
28
  "learning_rate": 0.0007,
29
  "tensorboard_log": null,
30
  "_last_obs": {
31
  ":type:": "<class 'collections.OrderedDict'>",
32
+ ":serialized:": "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",
33
+ "achieved_goal": "[[ 0.35464403 -0.4209765 0.74236524]\n [-0.05456962 0.43509918 -0.16167873]\n [ 0.3003578 0.00575695 0.44407046]\n [-0.00243477 0.43534645 -0.17626718]]",
34
+ "desired_goal": "[[ 0.55697584 -1.1519816 1.2796006 ]\n [-0.87904215 1.6536325 -0.4239502 ]\n [ 0.15028057 -0.09300896 1.4668494 ]\n [ 0.14365081 0.38855305 -1.3604007 ]]",
35
+ "observation": "[[ 0.35464403 -0.4209765 0.74236524 0.8552837 -1.5902424 1.2858188 ]\n [-0.05456962 0.43509918 -0.16167873 -1.8454638 1.585892 -1.3799909 ]\n [ 0.3003578 0.00575695 0.44407046 0.46858191 -0.00818225 0.3716068 ]\n [-0.00243477 0.43534645 -0.17626718 -1.6910936 1.5807924 -1.2921109 ]]"
36
  },
37
  "_last_episode_starts": {
38
  ":type:": "<class 'numpy.ndarray'>",
 
40
  },
41
  "_last_original_obs": {
42
  ":type:": "<class 'collections.OrderedDict'>",
43
+ ":serialized:": "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",
44
  "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]]",
45
+ "desired_goal": "[[ 0.12470976 -0.10523586 0.07996694]\n [-0.0462494 0.13839617 0.14217725]\n [ 0.02877658 -0.0287992 0.01356436]\n [-0.09950796 0.00347412 0.17680907]]",
46
  "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]]"
47
  },
48
  "_episode_num": 0,
 
52
  "_stats_window_size": 100,
53
  "ep_info_buffer": {
54
  ":type:": "<class 'collections.deque'>",
55
+ ":serialized:": "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"
56
  },
57
  "ep_success_buffer": {
58
  ":type:": "<class 'collections.deque'>",
59
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
60
  },
61
+ "_n_updates": 50000,
62
  "n_steps": 5,
63
  "gamma": 0.99,
64
  "gae_lambda": 1.0,
a2c-PandaReachDense-v3/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e15a54b2649fef3f7d0ae5f0304f3d3f3ae4f74e94b9f159cd119c34bb9e3764
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d7d391ed7afed5ad999d45bcacf24f760211ea93358899f53e8b240b9c108be6
3
  size 44734
a2c-PandaReachDense-v3/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:1315a3ad637f72d4f3646654fbcbacb1ad30b317b32253796429096caa93da30
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bb9cdd8f8870b26ef9016fb5b1544e9a98f74924614919027cd2ff7e5288e712
3
  size 46014
config.json CHANGED
@@ -1 +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 0x795ccc60de10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x795ccc6062c0>"}, "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": 100000, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1697024267864724591, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.20093498 -0.18957357 0.09378213]\n [-0.8835499 0.19210936 -1.0430254 ]\n [ 0.02261676 0.02432236 0.32938737]\n [-0.5342337 0.6523512 -0.55964124]]", "desired_goal": "[[ 0.23513773 -1.1786981 -0.24170214]\n [-1.5322638 0.391578 -1.5018995 ]\n [ 0.10614126 -1.1672944 0.0847332 ]\n [-0.15690142 0.97975844 -1.2024734 ]]", "observation": "[[-0.20093498 -0.18957357 0.09378213 -1.2458042 -1.8696011 -0.82258666]\n [-0.8835499 0.19210936 -1.0430254 -1.9137871 -1.0158666 -1.1267449 ]\n [ 0.02261676 0.02432236 0.32938737 0.23782827 -0.00500925 0.17554484]\n [-0.5342337 0.6523512 -0.55964124 -1.1704416 1.1311779 -1.0844946 ]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAQCUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[ 0.10391861 0.12532616 0.19721194]\n [-0.03183095 0.06693086 0.03856337]\n [ 0.00167038 -0.10475341 0.08401383]\n [-0.02432316 0.131114 0.2993231 ]]", "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": 5000, "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 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
 
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 0x795ccc60de10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x795ccc6062c0>"}, "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": 1697024770975973009, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.35464403 -0.4209765 0.74236524]\n [-0.05456962 0.43509918 -0.16167873]\n [ 0.3003578 0.00575695 0.44407046]\n [-0.00243477 0.43534645 -0.17626718]]", "desired_goal": "[[ 0.55697584 -1.1519816 1.2796006 ]\n [-0.87904215 1.6536325 -0.4239502 ]\n [ 0.15028057 -0.09300896 1.4668494 ]\n [ 0.14365081 0.38855305 -1.3604007 ]]", "observation": "[[ 0.35464403 -0.4209765 0.74236524 0.8552837 -1.5902424 1.2858188 ]\n [-0.05456962 0.43509918 -0.16167873 -1.8454638 1.585892 -1.3799909 ]\n [ 0.3003578 0.00575695 0.44407046 0.46858191 -0.00818225 0.3716068 ]\n [-0.00243477 0.43534645 -0.17626718 -1.6910936 1.5807924 -1.2921109 ]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAQCUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[ 0.12470976 -0.10523586 0.07996694]\n [-0.0462494 0.13839617 0.14217725]\n [ 0.02877658 -0.0287992 0.01356436]\n [-0.09950796 0.00347412 0.17680907]]", "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 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
replay.mp4 ADDED
Binary file (660 kB). View file
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -0.22085547130554914, "std_reward": 0.10937579407546594, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-11T11:42:54.986606"}
 
1
+ {"mean_reward": -0.21388578563928604, "std_reward": 0.12363799357431005, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-11T12:29:22.741266"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:23be28a07352166343b4532709b5d4dcf9f576bfb9dd6aaafcdc8d94e9767361
3
  size 2623
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d5d2e8546218410d4aacf5054407838e20eb84bb168f7a9ee678b567540ff562
3
  size 2623