jgalego aj555 commited on
Commit
4fb5e76
0 Parent(s):

Duplicate from aj555/a2c-PandaReachDense-v2

Browse files

Co-authored-by: Andrew Johnson <aj555@users.noreply.huggingface.co>

.gitattributes ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
5
+ *.ckpt filter=lfs diff=lfs merge=lfs -text
6
+ *.ftz filter=lfs diff=lfs merge=lfs -text
7
+ *.gz filter=lfs diff=lfs merge=lfs -text
8
+ *.h5 filter=lfs diff=lfs merge=lfs -text
9
+ *.joblib filter=lfs diff=lfs merge=lfs -text
10
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
11
+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
12
+ *.model filter=lfs diff=lfs merge=lfs -text
13
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
14
+ *.npy filter=lfs diff=lfs merge=lfs -text
15
+ *.npz filter=lfs diff=lfs merge=lfs -text
16
+ *.onnx filter=lfs diff=lfs merge=lfs -text
17
+ *.ot filter=lfs diff=lfs merge=lfs -text
18
+ *.parquet filter=lfs diff=lfs merge=lfs -text
19
+ *.pb filter=lfs diff=lfs merge=lfs -text
20
+ *.pickle filter=lfs diff=lfs merge=lfs -text
21
+ *.pkl filter=lfs diff=lfs merge=lfs -text
22
+ *.pt filter=lfs diff=lfs merge=lfs -text
23
+ *.pth filter=lfs diff=lfs merge=lfs -text
24
+ *.rar filter=lfs diff=lfs merge=lfs -text
25
+ *.safetensors filter=lfs diff=lfs merge=lfs -text
26
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
27
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
28
+ *.tflite filter=lfs diff=lfs merge=lfs -text
29
+ *.tgz filter=lfs diff=lfs merge=lfs -text
30
+ *.wasm filter=lfs diff=lfs merge=lfs -text
31
+ *.xz filter=lfs diff=lfs merge=lfs -text
32
+ *.zip filter=lfs diff=lfs merge=lfs -text
33
+ *.zst filter=lfs diff=lfs merge=lfs -text
34
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - PandaReachDense-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: A2C
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: PandaReachDense-v2
16
+ type: PandaReachDense-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: '-0.78 +/- 0.31'
20
+ name: mean_reward
21
+ verified: false
22
+ duplicated_from: aj555/a2c-PandaReachDense-v2
23
+ ---
24
+
25
+ # **A2C** Agent playing **PandaReachDense-v2**
26
+ This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
27
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
28
+
29
+ ## Usage (with Stable-baselines3)
30
+ TODO: Add your code
31
+
32
+
33
+ ```python
34
+ from stable_baselines3 import ...
35
+ from huggingface_sb3 import load_from_hub
36
+
37
+ ...
38
+ ```
a2c-PandaReachDense-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:544061e27fcdf1a7f7e6c7a0d3d544d1ecedfb46ed98fb91eab95c60a5a8dcf4
3
+ size 108170
a2c-PandaReachDense-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
a2c-PandaReachDense-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f3f38dcaee0>",
8
+ "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc_data object at 0x7f3f38dc5f30>"
10
+ },
11
+ "verbose": 1,
12
+ "policy_kwargs": {
13
+ ":type:": "<class 'dict'>",
14
+ ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
15
+ "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
16
+ "optimizer_kwargs": {
17
+ "alpha": 0.99,
18
+ "eps": 1e-05,
19
+ "weight_decay": 0
20
+ }
21
+ },
22
+ "observation_space": {
23
+ ":type:": "<class 'gym.spaces.dict.Dict'>",
24
+ ":serialized:": "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",
25
+ "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))])",
26
+ "_shape": null,
27
+ "dtype": null,
28
+ "_np_random": null
29
+ },
30
+ "action_space": {
31
+ ":type:": "<class 'gym.spaces.box.Box'>",
32
+ ":serialized:": "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",
33
+ "dtype": "float32",
34
+ "_shape": [
35
+ 3
36
+ ],
37
+ "low": "[-1. -1. -1.]",
38
+ "high": "[1. 1. 1.]",
39
+ "bounded_below": "[ True True True]",
40
+ "bounded_above": "[ True True True]",
41
+ "_np_random": null
42
+ },
43
+ "n_envs": 4,
44
+ "num_timesteps": 1000000,
45
+ "_total_timesteps": 1000000,
46
+ "_num_timesteps_at_start": 0,
47
+ "seed": null,
48
+ "action_noise": null,
49
+ "start_time": 1675184289646069857,
50
+ "learning_rate": 0.0007,
51
+ "tensorboard_log": null,
52
+ "lr_schedule": {
53
+ ":type:": "<class 'function'>",
54
+ ":serialized:": "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"
55
+ },
56
+ "_last_obs": {
57
+ ":type:": "<class 'collections.OrderedDict'>",
58
+ ":serialized:": "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",
59
+ "achieved_goal": "[[0.38291404 0.02198694 0.54587185]\n [0.38291404 0.02198694 0.54587185]\n [0.38291404 0.02198694 0.54587185]\n [0.38291404 0.02198694 0.54587185]]",
60
+ "desired_goal": "[[ 0.56465966 -0.9805096 -0.98330915]\n [ 0.2863216 0.67298603 -0.46499017]\n [-1.6413563 -0.721479 1.2246555 ]\n [ 0.66176635 -1.0003306 0.94696456]]",
61
+ "observation": "[[ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]\n [ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]\n [ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]\n [ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]]"
62
+ },
63
+ "_last_episode_starts": {
64
+ ":type:": "<class 'numpy.ndarray'>",
65
+ ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
66
+ },
67
+ "_last_original_obs": {
68
+ ":type:": "<class 'collections.OrderedDict'>",
69
+ ":serialized:": "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",
70
+ "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]]",
71
+ "desired_goal": "[[-0.02375822 -0.06565096 0.2683724 ]\n [-0.09780914 0.12904637 0.23852295]\n [-0.1096063 -0.00389551 0.21248126]\n [-0.01178128 0.13824888 0.06994968]]",
72
+ "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]]"
73
+ },
74
+ "_episode_num": 0,
75
+ "use_sde": false,
76
+ "sde_sample_freq": -1,
77
+ "_current_progress_remaining": 0.0,
78
+ "ep_info_buffer": {
79
+ ":type:": "<class 'collections.deque'>",
80
+ ":serialized:": "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"
81
+ },
82
+ "ep_success_buffer": {
83
+ ":type:": "<class 'collections.deque'>",
84
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
+ },
86
+ "_n_updates": 50000,
87
+ "n_steps": 5,
88
+ "gamma": 0.99,
89
+ "gae_lambda": 1.0,
90
+ "ent_coef": 0.0,
91
+ "vf_coef": 0.5,
92
+ "max_grad_norm": 0.5,
93
+ "normalize_advantage": false
94
+ }
a2c-PandaReachDense-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2651e79b11866fc8bc5b6c04dc8084cb0f87f0e6ae3d0f8498880dbfc2c11451
3
+ size 44734
a2c-PandaReachDense-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:17f110c3adae7f63e6abc8cc2712742a62836216babd77c8db8c1a48821dede8
3
+ size 46014
a2c-PandaReachDense-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
a2c-PandaReachDense-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.0-58-generic-x86_64-with-glibc2.17 # 64~20.04.1-Ubuntu SMP Fri Jan 6 16:42:31 UTC 2023
2
+ - Python: 3.8.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
config.json ADDED
@@ -0,0 +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 0x7f3f38dcaee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f3f38dc5f30>"}, "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": 1675184289646069857, "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": "[[0.38291404 0.02198694 0.54587185]\n [0.38291404 0.02198694 0.54587185]\n [0.38291404 0.02198694 0.54587185]\n [0.38291404 0.02198694 0.54587185]]", "desired_goal": "[[ 0.56465966 -0.9805096 -0.98330915]\n [ 0.2863216 0.67298603 -0.46499017]\n [-1.6413563 -0.721479 1.2246555 ]\n [ 0.66176635 -1.0003306 0.94696456]]", "observation": "[[ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]\n [ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]\n [ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]\n [ 3.8291404e-01 2.1986937e-02 5.4587185e-01 2.6572803e-03\n 2.1756943e-03 -2.0043520e-04]]"}, "_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": "[[-0.02375822 -0.06565096 0.2683724 ]\n [-0.09780914 0.12904637 0.23852295]\n [-0.1096063 -0.00389551 0.21248126]\n [-0.01178128 0.13824888 0.06994968]]", "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-5.15.0-58-generic-x86_64-with-glibc2.17 # 64~20.04.1-Ubuntu SMP Fri Jan 6 16:42:31 UTC 2023", "Python": "3.8.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
replay.mp4 ADDED
Binary file (335 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -0.7804141158703715, "std_reward": 0.30845685466311107, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-31T12:24:45.339691"}
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c437e1ef7968c2d0e45c7f89f028e5338831087c000efcd47117203219c3f9ed
3
+ size 3056