Hugging Face's logo

amannlp
/
a2c-PandaReachDense-v2

Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results
Model card Files Community
1
amannlp commited on
Commit
66e5021
•
1 Parent(s): 024232b

second commit

Browse files
Files changed (8) hide show
  1. README.md +1 -1
  2. a2c-PandaReachDense-v2.zip +2 -2
  3. a2c-PandaReachDense-v2/data +11 -11
  4. a2c-PandaReachDense-v2/policy.optimizer.pth +1 -1
  5. a2c-PandaReachDense-v2/policy.pth +1 -1
  6. config.json +1 -1
  7. results.json +1 -1
  8. vec_normalize.pkl +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
- value: -3.36 +/- 0.97
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -22.68 +/- 9.59
20
  name: mean_reward
21
  verified: false
22
  ---
a2c-PandaReachDense-v2.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:fbd930153d3149666a0004e4f69dfd02cd57c2649968be6574f63c7de888ff5a
3
- size 108078
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3b90bb370fe5d682896a4f6d64f099c1f464d407f86fa7d37dc5227ac6f20438
3
+ size 108074
a2c-PandaReachDense-v2/data CHANGED
@@ -19,12 +19,12 @@
19
  "weight_decay": 0
20
  }
21
  },
22
- "num_timesteps": 683868,
23
  "_total_timesteps": 1000000,
24
  "_num_timesteps_at_start": 0,
25
  "seed": null,
26
  "action_noise": null,
27
- "start_time": 1685227871413441300,
28
  "learning_rate": 0.0007,
29
  "tensorboard_log": null,
30
  "lr_schedule": {
@@ -33,10 +33,10 @@
33
  },
34
  "_last_obs": {
35
  ":type:": "<class 'collections.OrderedDict'>",
36
- ":serialized:": "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",
37
- "achieved_goal": "[[ 1.1354738 -1.755725 1.2038628 ]\n [ 0.5475919 0.52993697 -0.8696667 ]\n [-0.5306962 0.27415785 -0.0126167 ]\n [ 0.5534818 -1.6940697 1.2986264 ]]",
38
- "desired_goal": "[[ 1.0838336 -1.5767784 0.93825483]\n [ 1.2769777 0.7140147 0.23233928]\n [-0.9635132 -0.03041154 0.25008795]\n [ 0.32717067 -1.6930838 1.3558333 ]]",
39
- "observation": "[[ 1.1354738 -1.755725 1.2038628 -0.376704 -0.04096746 0.71821344]\n [ 0.5475919 0.52993697 -0.8696667 0.6437391 0.3991467 0.4505098 ]\n [-0.5306962 0.27415785 -0.0126167 0.977082 0.13312724 1.8373626 ]\n [ 0.5534818 -1.6940697 1.2986264 -2.2456274 -0.7789596 -2.074173 ]]"
40
  },
41
  "_last_episode_starts": {
42
  ":type:": "<class 'numpy.ndarray'>",
@@ -44,25 +44,25 @@
44
  },
45
  "_last_original_obs": {
46
  ":type:": "<class 'collections.OrderedDict'>",
47
- ":serialized:": "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",
48
  "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]]",
49
- "desired_goal": "[[-0.00703509 0.11490088 0.15121311]\n [ 0.05514611 0.07136056 0.04918185]\n [ 0.01838838 -0.02801351 0.19756538]\n [ 0.00855516 0.11481028 0.13485304]]",
50
  "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]]"
51
  },
52
  "_episode_num": 0,
53
  "use_sde": false,
54
  "sde_sample_freq": -1,
55
- "_current_progress_remaining": 0.31614,
56
  "_stats_window_size": 100,
57
  "ep_info_buffer": {
58
  ":type:": "<class 'collections.deque'>",
59
- ":serialized:": "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"
60
  },
61
  "ep_success_buffer": {
62
  ":type:": "<class 'collections.deque'>",
63
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
64
  },
65
- "_n_updates": 34193,
66
  "n_steps": 5,
67
  "gamma": 0.99,
68
  "gae_lambda": 1.0,
 
19
  "weight_decay": 0
20
  }
21
  },
22
+ "num_timesteps": 10712,
23
  "_total_timesteps": 1000000,
24
  "_num_timesteps_at_start": 0,
25
  "seed": null,
26
  "action_noise": null,
27
+ "start_time": 1685230809556197235,
28
  "learning_rate": 0.0007,
29
  "tensorboard_log": null,
30
  "lr_schedule": {
 
33
  },
34
  "_last_obs": {
35
  ":type:": "<class 'collections.OrderedDict'>",
36
+ ":serialized:": "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",
37
+ "achieved_goal": "[[ 1.1657512 -0.29724422 -0.56844985]\n [ 0.20062685 0.95045495 -0.07383783]\n [-3.1922247 1.2108992 -0.31441495]\n [ 0.9124428 -1.4586957 -0.21392094]]",
38
+ "desired_goal": "[[-0.56000525 0.90902436 1.0563488 ]\n [-1.2917004 1.682299 1.6394899 ]\n [-1.0668166 0.06415579 -1.6067684 ]\n [ 1.6800156 -0.5735194 1.612862 ]]",
39
+ "observation": "[[ 1.1657512 -0.29724422 -0.56844985 0.51323324 -1.4144022 1.2779937 ]\n [ 0.20062685 0.95045495 -0.07383783 1.0798455 -1.8037567 0.00554135]\n [-3.1922247 1.2108992 -0.31441495 0.5045848 0.5053174 0.73417705]\n [ 0.9124428 -1.4586957 -0.21392094 -0.00442377 -0.51394564 0.20178121]]"
40
  },
41
  "_last_episode_starts": {
42
  ":type:": "<class 'numpy.ndarray'>",
 
44
  },
45
  "_last_original_obs": {
46
  ":type:": "<class 'collections.OrderedDict'>",
47
+ ":serialized:": "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",
48
  "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]]",
49
+ "desired_goal": "[[ 0.08720823 0.1433123 0.01334852]\n [-0.07040402 -0.1493951 0.27035478]\n [ 0.08392576 -0.11646712 0.22350162]\n [-0.11007939 0.08844441 0.04795517]]",
50
  "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]]"
51
  },
52
  "_episode_num": 0,
53
  "use_sde": false,
54
  "sde_sample_freq": -1,
55
+ "_current_progress_remaining": 0.9893,
56
  "_stats_window_size": 100,
57
  "ep_info_buffer": {
58
  ":type:": "<class 'collections.deque'>",
59
+ ":serialized:": "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"
60
  },
61
  "ep_success_buffer": {
62
  ":type:": "<class 'collections.deque'>",
63
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
64
  },
65
+ "_n_updates": 535,
66
  "n_steps": 5,
67
  "gamma": 0.99,
68
  "gae_lambda": 1.0,
a2c-PandaReachDense-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:c17ef2a03979301f657948df47ac6221460ed941479edf0044b15a7595168905
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aa15ee78c283526cf566b3857d47315e9866e49d4ba1fba5325827c7606867ef
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a6f004f02eea7fe23d786c1daddbc9d90d43501d756c1ee5e7baef8f56ae9419
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:be9527c05b3c4fa5bf3c66a3ea8244d0fdc34d619c5f68a52ba41c865a497db6
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 0x7f2283106050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2283102d00>"}, "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": 683868, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685227871413441300, "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": "[[ 1.1354738 -1.755725 1.2038628 ]\n [ 0.5475919 0.52993697 -0.8696667 ]\n [-0.5306962 0.27415785 -0.0126167 ]\n [ 0.5534818 -1.6940697 1.2986264 ]]", "desired_goal": "[[ 1.0838336 -1.5767784 0.93825483]\n [ 1.2769777 0.7140147 0.23233928]\n [-0.9635132 -0.03041154 0.25008795]\n [ 0.32717067 -1.6930838 1.3558333 ]]", "observation": "[[ 1.1354738 -1.755725 1.2038628 -0.376704 -0.04096746 0.71821344]\n [ 0.5475919 0.52993697 -0.8696667 0.6437391 0.3991467 0.4505098 ]\n [-0.5306962 0.27415785 -0.0126167 0.977082 0.13312724 1.8373626 ]\n [ 0.5534818 -1.6940697 1.2986264 -2.2456274 -0.7789596 -2.074173 ]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[-0.00703509 0.11490088 0.15121311]\n [ 0.05514611 0.07136056 0.04918185]\n [ 0.01838838 -0.02801351 0.19756538]\n [ 0.00855516 0.11481028 0.13485304]]", "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": 0.31614, "_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": 34193, "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:": "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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"}}
 
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 0x7f2283106050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2283102d00>"}, "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": 10712, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685230809556197235, "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": "[[ 1.1657512 -0.29724422 -0.56844985]\n [ 0.20062685 0.95045495 -0.07383783]\n [-3.1922247 1.2108992 -0.31441495]\n [ 0.9124428 -1.4586957 -0.21392094]]", "desired_goal": "[[-0.56000525 0.90902436 1.0563488 ]\n [-1.2917004 1.682299 1.6394899 ]\n [-1.0668166 0.06415579 -1.6067684 ]\n [ 1.6800156 -0.5735194 1.612862 ]]", "observation": "[[ 1.1657512 -0.29724422 -0.56844985 0.51323324 -1.4144022 1.2779937 ]\n [ 0.20062685 0.95045495 -0.07383783 1.0798455 -1.8037567 0.00554135]\n [-3.1922247 1.2108992 -0.31441495 0.5045848 0.5053174 0.73417705]\n [ 0.9124428 -1.4586957 -0.21392094 -0.00442377 -0.51394564 0.20178121]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[ 0.08720823 0.1433123 0.01334852]\n [-0.07040402 -0.1493951 0.27035478]\n [ 0.08392576 -0.11646712 0.22350162]\n [-0.11007939 0.08844441 0.04795517]]", "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": 0.9893, "_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": 535, "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:": "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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 CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -3.362027208087966, "std_reward": 0.9698663687082459, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-27T23:25:26.500254"}
 
1
+ {"mean_reward": -22.679593806155026, "std_reward": 9.590064848551899, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-27T23:40:51.257421"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:1e825c78fa3e516b8f57949a583221d6f81eabc0a137bfa289f1f8bad6129acc
3
  size 2387
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5715b66049fb8a92486d73054f60f52434bc49a448257e6db6cf5bb40a4f4e6e
3
  size 2387