AlinaKozyreva commited on
Commit
f17dde0
1 Parent(s): e3efe38

Upload PPO HalfCheetah-v4 trained agent

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ replay.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - HalfCheetah-v4
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: HalfCheetah-v4
16
+ type: HalfCheetah-v4
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 3245.03 +/- 846.50
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **HalfCheetah-v4**
25
+ This is a trained model of a **PPO** agent playing **HalfCheetah-v4**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n 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\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: Features extractor to use.\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 ActorCriticPolicy.__init__ at 0x7f79f737cca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f79f737cd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f79f737cdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f79f737ce50>", "_build": "<function ActorCriticPolicy._build at 0x7f79f737cee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f79f737cf70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f79f737d000>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f79f737d090>", "_predict": "<function ActorCriticPolicy._predict at 0x7f79f737d120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f79f737d1b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f79f737d240>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f79f737d2d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f79f7378d00>"}, "verbose": 0, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVjgAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA1hY3RpdmF0aW9uX2ZulIwbdG9yY2gubm4ubW9kdWxlcy5hY3RpdmF0aW9ulIwEUmVMVZSTlIwIbmV0X2FyY2iUXZR9lCiMAnBplF2UKE0AAU0AAWWMAnZmlF2UKE0AAU0AAWV1YXUu", "log_std_init": -2, "ortho_init": false, "activation_fn": "<class 'torch.nn.modules.activation.ReLU'>", "net_arch": [{"pi": [256, 256], "vf": [256, 256]}]}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711945142323081078, "learning_rate": 1e-05, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV/QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaIAAAAAAAAANQpRkX3Ub+/BJsxdqED8T9fQ0sfBKK0P0hEj/ZE7tG/2nhzVN3yvj9XuSs+GrbMP5Az2NFUT9o/UsM2Qtl8qD/6oRJ/6mepvxbZQWuHMMM/HgG45qXtsT8QjcEGE52wvy5bUPwz2glAVpSqKq/uBkCY14hUdoHjvwE4mfiBBP8/83EVIsL7CcCUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLEYaUjAFDlHSUUpQu"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 39080, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float64", "bounded_below": "[False False False False False False False False False False False False\n False False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False]", "_shape": [17], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]", "low_repr": "-inf", "high_repr": "inf", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True]", "bounded_above": "[ True True True True True True]", "_shape": [6], "low": "[-1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 1, "n_steps": 512, "gamma": 0.98, "gae_lambda": 0.92, "ent_coef": 0.01, "vf_coef": 0.58096, "max_grad_norm": 0.8, "batch_size": 64, "n_epochs": 20, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-HalfCheetah-v4.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4e0d9e355de624414834cec064d18894db40b59313e11ed918c8233fa083e8c4
3
+ size 1743057
ppo-HalfCheetah-v4/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-HalfCheetah-v4/data ADDED
@@ -0,0 +1,123 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__doc__": "\n 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\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: Features extractor to use.\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 ActorCriticPolicy.__init__ at 0x7f79f737cca0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f79f737cd30>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f79f737cdc0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f79f737ce50>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f79f737cee0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f79f737cf70>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f79f737d000>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f79f737d090>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f79f737d120>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f79f737d1b0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f79f737d240>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f79f737d2d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f79f7378d00>"
21
+ },
22
+ "verbose": 0,
23
+ "policy_kwargs": {
24
+ ":type:": "<class 'dict'>",
25
+ ":serialized:": "gAWVjgAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA1hY3RpdmF0aW9uX2ZulIwbdG9yY2gubm4ubW9kdWxlcy5hY3RpdmF0aW9ulIwEUmVMVZSTlIwIbmV0X2FyY2iUXZR9lCiMAnBplF2UKE0AAU0AAWWMAnZmlF2UKE0AAU0AAWV1YXUu",
26
+ "log_std_init": -2,
27
+ "ortho_init": false,
28
+ "activation_fn": "<class 'torch.nn.modules.activation.ReLU'>",
29
+ "net_arch": [
30
+ {
31
+ "pi": [
32
+ 256,
33
+ 256
34
+ ],
35
+ "vf": [
36
+ 256,
37
+ 256
38
+ ]
39
+ }
40
+ ]
41
+ },
42
+ "num_timesteps": 1000448,
43
+ "_total_timesteps": 1000000,
44
+ "_num_timesteps_at_start": 0,
45
+ "seed": null,
46
+ "action_noise": null,
47
+ "start_time": 1711945142323081078,
48
+ "learning_rate": 1e-05,
49
+ "tensorboard_log": null,
50
+ "_last_obs": {
51
+ ":type:": "<class 'numpy.ndarray'>",
52
+ ":serialized:": "gAWV/QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaIAAAAAAAAANQpRkX3Ub+/BJsxdqED8T9fQ0sfBKK0P0hEj/ZE7tG/2nhzVN3yvj9XuSs+GrbMP5Az2NFUT9o/UsM2Qtl8qD/6oRJ/6mepvxbZQWuHMMM/HgG45qXtsT8QjcEGE52wvy5bUPwz2glAVpSqKq/uBkCY14hUdoHjvwE4mfiBBP8/83EVIsL7CcCUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLEYaUjAFDlHSUUpQu"
53
+ },
54
+ "_last_episode_starts": {
55
+ ":type:": "<class 'numpy.ndarray'>",
56
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
57
+ },
58
+ "_last_original_obs": null,
59
+ "_episode_num": 0,
60
+ "use_sde": false,
61
+ "sde_sample_freq": -1,
62
+ "_current_progress_remaining": -0.00044800000000000395,
63
+ "_stats_window_size": 100,
64
+ "ep_info_buffer": {
65
+ ":type:": "<class 'collections.deque'>",
66
+ ":serialized:": "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"
67
+ },
68
+ "ep_success_buffer": {
69
+ ":type:": "<class 'collections.deque'>",
70
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
71
+ },
72
+ "_n_updates": 39080,
73
+ "observation_space": {
74
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
75
+ ":serialized:": "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",
76
+ "dtype": "float64",
77
+ "bounded_below": "[False False False False False False False False False False False False\n False False False False False]",
78
+ "bounded_above": "[False False False False False False False False False False False False\n False False False False False]",
79
+ "_shape": [
80
+ 17
81
+ ],
82
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf]",
83
+ "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]",
84
+ "low_repr": "-inf",
85
+ "high_repr": "inf",
86
+ "_np_random": null
87
+ },
88
+ "action_space": {
89
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
90
+ ":serialized:": "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",
91
+ "dtype": "float32",
92
+ "bounded_below": "[ True True True True True True]",
93
+ "bounded_above": "[ True True True True True True]",
94
+ "_shape": [
95
+ 6
96
+ ],
97
+ "low": "[-1. -1. -1. -1. -1. -1.]",
98
+ "high": "[1. 1. 1. 1. 1. 1.]",
99
+ "low_repr": "-1.0",
100
+ "high_repr": "1.0",
101
+ "_np_random": null
102
+ },
103
+ "n_envs": 1,
104
+ "n_steps": 512,
105
+ "gamma": 0.98,
106
+ "gae_lambda": 0.92,
107
+ "ent_coef": 0.01,
108
+ "vf_coef": 0.58096,
109
+ "max_grad_norm": 0.8,
110
+ "batch_size": 64,
111
+ "n_epochs": 20,
112
+ "clip_range": {
113
+ ":type:": "<class 'function'>",
114
+ ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz+5mZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
115
+ },
116
+ "clip_range_vf": null,
117
+ "normalize_advantage": true,
118
+ "target_kl": null,
119
+ "lr_schedule": {
120
+ ":type:": "<class 'function'>",
121
+ ":serialized:": "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"
122
+ }
123
+ }
ppo-HalfCheetah-v4/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1f209171b66c3493ebd22d9a1e829f0c68e713d0527cba98c71e352f013544d5
3
+ size 1151201
ppo-HalfCheetah-v4/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2bb0742ccd06ef9318517a4a0fe6b801e23ea306bcc9de5323c22c26773b0813
3
+ size 575215
ppo-HalfCheetah-v4/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-HalfCheetah-v4/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.2.1+cu121
5
+ - GPU Enabled: False
6
+ - Numpy: 1.25.2
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d9571faa2674ee779d6fd027abc3bf0b9472c5711afc0a978f8564f2523dfc5f
3
+ size 1769101
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 3245.0291625069804, "std_reward": 846.5035921533137, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-01T05:15:08.359993"}