Hugging Face's logo

sb3
/
a2c-HopperBulletEnv-v0

Reinforcement Learning
stable-baselines3
HopperBulletEnv-v0
deep-reinforcement-learning
Eval Results
Model card Files Community
araffin commited on
Commit
e4fa3d3
•
1 Parent(s): 9c4a063

Initial commit

Browse files
Files changed (16) hide show
  1. .gitattributes +2 -0
  2. README.md +70 -0
  3. a2c-HopperBulletEnv-v0.zip +3 -0
  4. a2c-HopperBulletEnv-v0/_stable_baselines3_version +1 -0
  5. a2c-HopperBulletEnv-v0/data +106 -0
  6. a2c-HopperBulletEnv-v0/policy.optimizer.pth +3 -0
  7. a2c-HopperBulletEnv-v0/policy.pth +3 -0
  8. a2c-HopperBulletEnv-v0/pytorch_variables.pth +3 -0
  9. a2c-HopperBulletEnv-v0/system_info.txt +7 -0
  10. args.yml +59 -0
  11. config.yml +33 -0
  12. env_kwargs.yml +1 -0
  13. replay.mp4 +3 -0
  14. results.json +1 -0
  15. train_eval_metrics.zip +3 -0
  16. vec_normalize.pkl +3 -0
.gitattributes CHANGED
@@ -25,3 +25,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
29
+ vec_normalize.pkl filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,70 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - HopperBulletEnv-v0
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: A2C
10
+ results:
11
+ - metrics:
12
+ - type: mean_reward
13
+ value: 709.34 +/- 213.24
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: HopperBulletEnv-v0
20
+ type: HopperBulletEnv-v0
21
+ ---
22
+
23
+ # **A2C** Agent playing **HopperBulletEnv-v0**
24
+ This is a trained model of a **A2C** agent playing **HopperBulletEnv-v0**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
26
+ and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
27
+
28
+ The RL Zoo is a training framework for Stable Baselines3
29
+ reinforcement learning agents,
30
+ with hyperparameter optimization and pre-trained agents included.
31
+
32
+ ## Usage (with SB3 RL Zoo)
33
+
34
+ RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
35
+ SB3: https://github.com/DLR-RM/stable-baselines3<br/>
36
+ SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
37
+
38
+ ```
39
+ # Download model and save it into the logs/ folder
40
+ python -m utils.load_from_hub --algo a2c --env HopperBulletEnv-v0 -orga sb3 -f logs/
41
+ python enjoy.py --algo a2c --env HopperBulletEnv-v0 -f logs/
42
+ ```
43
+
44
+ ## Training (with the RL Zoo)
45
+ ```
46
+ python train.py --algo a2c --env HopperBulletEnv-v0 -f logs/
47
+ # Upload the model and generate video (when possible)
48
+ python -m utils.push_to_hub --algo a2c --env HopperBulletEnv-v0 -f logs/ -orga sb3
49
+ ```
50
+
51
+ ## Hyperparameters
52
+ ```python
53
+ OrderedDict([('ent_coef', 0.0),
54
+ ('env_wrapper', 'sb3_contrib.common.wrappers.TimeFeatureWrapper'),
55
+ ('gae_lambda', 0.9),
56
+ ('gamma', 0.99),
57
+ ('learning_rate', 'lin_0.00096'),
58
+ ('max_grad_norm', 0.5),
59
+ ('n_envs', 4),
60
+ ('n_steps', 8),
61
+ ('n_timesteps', 2000000.0),
62
+ ('normalize', True),
63
+ ('normalize_advantage', False),
64
+ ('policy', 'MlpPolicy'),
65
+ ('policy_kwargs', 'dict(log_std_init=-2, ortho_init=False)'),
66
+ ('use_rms_prop', True),
67
+ ('use_sde', True),
68
+ ('vf_coef', 0.4),
69
+ ('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])
70
+ ```
a2c-HopperBulletEnv-v0.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:961dfc78d8ffef06e91a7c0210a68119566c02b26e940bbb680fb821c31b2e00
3
+ size 115292
a2c-HopperBulletEnv-v0/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.1a8
a2c-HopperBulletEnv-v0/data ADDED
@@ -0,0 +1,106 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f70d2699950>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f70d26999e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f70d2699a70>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f70d2699b00>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f70d2699b90>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f70d2699c20>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f70d2699cb0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f70d2699d40>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f70d2699dd0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f70d2699e60>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f70d2699ef0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f70d26eb840>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {
23
+ ":type:": "<class 'dict'>",
24
+ ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
25
+ "log_std_init": -2,
26
+ "ortho_init": false,
27
+ "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
28
+ "optimizer_kwargs": {
29
+ "alpha": 0.99,
30
+ "eps": 1e-05,
31
+ "weight_decay": 0
32
+ }
33
+ },
34
+ "observation_space": {
35
+ ":type:": "<class 'gym.spaces.box.Box'>",
36
+ ":serialized:": "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",
37
+ "dtype": "float32",
38
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf 0.]",
39
+ "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 1.]",
40
+ "bounded_below": "[False False False False False False False False False False False False\n False False False True]",
41
+ "bounded_above": "[False False False False False False False False False False False False\n False False False True]",
42
+ "_np_random": null,
43
+ "_shape": [
44
+ 16
45
+ ]
46
+ },
47
+ "action_space": {
48
+ ":type:": "<class 'gym.spaces.box.Box'>",
49
+ ":serialized:": "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",
50
+ "dtype": "float32",
51
+ "low": "[-1. -1. -1.]",
52
+ "high": "[1. 1. 1.]",
53
+ "bounded_below": "[ True True True]",
54
+ "bounded_above": "[ True True True]",
55
+ "_np_random": "RandomState(MT19937)",
56
+ "_shape": [
57
+ 3
58
+ ]
59
+ },
60
+ "n_envs": 4,
61
+ "num_timesteps": 2000000,
62
+ "_total_timesteps": 2000000,
63
+ "_num_timesteps_at_start": 0,
64
+ "seed": 0,
65
+ "action_noise": null,
66
+ "start_time": 1614621275.3394907,
67
+ "learning_rate": {
68
+ ":type:": "<class 'function'>",
69
+ ":serialized:": "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"
70
+ },
71
+ "tensorboard_log": null,
72
+ "lr_schedule": {
73
+ ":type:": "<class 'function'>",
74
+ ":serialized:": "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"
75
+ },
76
+ "_last_obs": null,
77
+ "_last_episode_starts": null,
78
+ "_last_original_obs": {
79
+ ":type:": "<class 'numpy.ndarray'>",
80
+ ":serialized:": "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"
81
+ },
82
+ "_episode_num": 0,
83
+ "use_sde": true,
84
+ "sde_sample_freq": -1,
85
+ "_current_progress_remaining": 0.0,
86
+ "ep_info_buffer": {
87
+ ":type:": "<class 'collections.deque'>",
88
+ ":serialized:": "gASVEAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGM2ZVfeDWeMAWyUS1qMAXSUR0C3C2kliSaFdX2UKGgGR0B1T1bqyGBXaAdL12gIR0C3C4F4LThHdX2UKGgGR0B/icGyHEdeaAdNdgFoCEdAtwuJy+6AfHV9lChoBkdAdZRIEbHZK2gHS8poCEdAtw0JR3u/lHV9lChoBkdAZBFb9qDbrWgHS2doCEdAtw3SjesPrnV9lChoBkdAhOa3f642CWgHTfABaAhHQLcOwLM9r451fZQoaAZHQIG0USM98qpoB02xAWgIR0C3DtMurZJ1dX2UKGgGR0Bq4c1l5GBnaAdLe2gIR0C3D7DBZZB+dX2UKGgGR0CCoy50bLlnaAdNfAFoCEdAtxC1Xo1UEXV9lChoBkdAkFK2AkLQX2gHTcACaAhHQLcQw3Ov+wV1fZQoaAZHQHLv9/BnBcloB0ugaAhHQLcQ6nQ6ZIB1fZQoaAZHQG0oGMGX5WRoB0uMaAhHQLcZn7mMfih1fZQoaAZHQIX7voX9BKNoB02xAWgIR0C3Gca/VRUFdX2UKGgGR0Bt3ATAWSEEaAdLkmgIR0C3GuLgXMyKdX2UKGgGR0BiEZRjz7MxaAdLTmgIR0C3G3sJQcghdX2UKGgGR0CG7RcpsoDxaAdNyQFoCEdAtxvjabnX/nV9lChoBkdAZQV8D0UXYWgHS2ZoCEdAtxxAqYqoZXV9lChoBkdAceIL3K0UoWgHS8BoCEdAtx1ZYaHbh3V9lChoBkdAfDpnE2pAEGgHTS0BaAhHQLceij6N2kl1fZQoaAZHQJcuql3yI55oB03oA2gIR0C3H/TxoZhsdX2UKGgGR0CSqLxCY1HfaAdNRwNoCEdAtyAAztTkyXV9lChoBkdAd+cCT2WY4WgHTQkBaAhHQLciAsP8Q7N1fZQoaAZHQIMFhSHdoFpoB03wAWgIR0C3Ik6MBIWhdX2UKGgGR0Buuh2yLQ5WaAdLkWgIR0C3Ix1ev6j4dX2UKGgGR0BpUHuiN83NaAdLhWgIR0C3I1HhGYrsdX2UKGgGR0BhfIJ9iMHbaAdLVmgIR0C3I8StV7x/dX2UKGgGR0CJJ9O6/ZdwaAdNGAJoCEdAtyQLhXKbKHV9lChoBkdAk+e27Wd3CGgHTaUDaAhHQLckdD3/PxB1fZQoaAZHQHH/VQuVX3hoB0vBaAhHQLclhAvL5h11fZQoaAZHQHjgNkz41xdoB00sAWgIR0C3JhMYVIqcdX2UKGgGR0CDGn/+85CGaAdNigFoCEdAtyZWHYYixHV9lChoBkdAcjTwNsnAqWgHS7doCEdAtye54KQaJnV9lChoBkdAZYAQL/jsEGgHS2FoCEdAtyh3CBPKuHV9lChoBkdAgNPBltj0+WgHTUgBaAhHQLcokXAdn011fZQoaAZHQGhRiUHIIWxoB0tnaAhHQLcpXfFrEcd1fZQoaAZHQG6HJTVDrqtoB0uaaAhHQLcqi2fkFOh1fZQoaAZHQI6CNFQVKwpoB02rAmgIR0C3Kr1otcv/dX2UKGgGR0CO2thzeXRgaAdNRQNoCEdAtyrZdHDrJXV9lChoBkdAXx8vwmVqvmgHS0loCEdAtysaCEpRXXV9lChoBkdAc6XhlDneSGgHS8poCEdAtzQQvwmVq3V9lChoBkdAiHUyon8baWgHTToCaAhHQLc0nT1CgK51fZQoaAZHQGgN2TPjXFtoB0twaAhHQLc064c3l0Z1fZQoaAZHQICZrvTgEU1oB01PAWgIR0C3NXJR8+ibdX2UKGgGR0BmlRbMX7+DaAdLbWgIR0C3NcGsmv4edX2UKGgGR0CKOc/FirksaAdNJgJoCEdAtzbSJ79hqnV9lChoBkdAcvBHy3CsO2gHS8JoCEdAtzbrdAPd23V9lChoBkdAfQevWYnfEWgHTT4BaAhHQLc3Cjo6jnF1fZQoaAZHQGjBBZ6lchVoB0ttaAhHQLc3qC2MKkV1fZQoaAZHQHrZH0K7ZnNoB00MAWgIR0C3N8rFCLMtdX2UKGgGR0Bk80rsjVx0aAdLfGgIR0C3OL5Oi35OdX2UKGgGR0ByZWLpA2Q5aAdLn2gIR0C3ON8Uh3aBdX2UKGgGR0BOpml67dzoaAdLJWgIR0C3OShZ6lchdX2UKGgGR0Bu1Vz8xbjcaAdLlWgIR0C3OeA00m+kdX2UKGgGR0CHfB/HYHxCaAdN+AFoCEdAtzrh41P3z3V9lChoBkdAdmOGA08/2WgHS+NoCEdAtzriz0HyE3V9lChoBkdAeoSnjQzDXWgHTSEBaAhHQLc8EptJnQJ1fZQoaAZHQHBrOaOPvKFoB0uYaAhHQLc9Or92ovV1fZQoaAZHQIKZPBguyu9oB01yAWgIR0C3PbLEgntwdX2UKGgGR0CERmWCVbA2aAdN2AFoCEdAtz55rJr+HnV9lChoBkdAlYb/8l5WzWgHTegDaAhHQLc+id43WFx1fZQoaAZHQFu+Jaq0dBBoB0s+aAhHQLc+8+9alk91fZQoaAZHQHCdifDk2gpoB0vKaAhHQLc/POKfnOl1fZQoaAZHQHLolPznRsxoB0uraAhHQLdAP0hvBJt1fZQoaAZHQHYueuJUHY9oB0vraAhHQLdAUqhlDnh1fZQoaAZHQHiV8Udq+JxoB0vgaAhHQLdA8JIUahp1fZQoaAZHQIMXqJ40Mw1oB00GAmgIR0C3QS2ALApKdX2UKGgGR0BpcGuLaVUuaAdLcmgIR0C3QdExh2GJdX2UKGgGR0B9Q6CPIXCTaAdNXgFoCEdAt0L/hegL7XV9lChoBkdAf3raF23az2gHTVQBaAhHQLdDxpB5X2d1fZQoaAZHQFuzTAWSEDhoB0tCaAhHQLdER0ngHeJ1fZQoaAZHQH3W0nogV45oB02eAWgIR0C3RPfeP7vYdX2UKGgGR0BtTuygPEsKaAdLmGgIR0C3RW+IVM24dX2UKGgGR0BR06T0QK8daAdLK2gIR0C3RcLH6uW9dX2UKGgGR0BzmoTVUdaMaAdLvmgIR0C3Tixguyu7dX2UKGgGR0CTs2FQl8gIaAdN6ANoCEdAt07V/c32mHV9lChoBkdAiAllQ2uPm2gHTSECaAhHQLdQFj0+TvB1fZQoaAZHQHIhfgNwzchoB0umaAhHQLdQGYIjW091fZQoaAZHQJQ8rRXwLE1oB01yA2gIR0C3UK0nCwbEdX2UKGgGR0BrRlZ/0/W2aAdLhGgIR0C3URgfyPMjdX2UKGgGR0B0Bzh60IC2aAdLuWgIR0C3UYPv4M4MdX2UKGgGR0CL1Jvy9VWCaAdNfQJoCEdAt1MIgpz90nV9lChoBkdAe0W0OEug6GgHTSoBaAhHQLdTyYMvysl1fZQoaAZHQGjdGReTmnxoB0t3aAhHQLdT8bpeNT91fZQoaAZHQH12ZDzAeq9oB01dAWgIR0C3VndKZlWfdX2UKGgGR0CSsiuX/o7naAdNQgNoCEdAt1cP889wFXV9lChoBkdAh8N/EXLvC2gHTd0BaAhHQLdXlmukk8l1fZQoaAZHQHG0thZyMk1oB0ubaAhHQLdXpCHymQ91fZQoaAZHQHGoHenAIppoB0uqaAhHQLdYWwnYxtZ1fZQoaAZHQG1zdwNsnAtoB0uLaAhHQLdYslBQemx1fZQoaAZHQJI27I1cdHVoB03oA2gIR0C3WLvIwM6SdX2UKGgGR0Bj5NopQUHqaAdLZ2gIR0C3WYUnTiKjdX2UKGgGR0Bg/uT7l7tzaAdLUGgIR0C3WiHY150KdX2UKGgGR0B7y+8wpON6aAdNUgFoCEdAt1oqR1X/53V9lChoBkdAe80TjvNNamgHTWIBaAhHQLdbDi4J/od1fZQoaAZHQGS4HOSntOVoB0tiaAhHQLdbzPrv9cd1fZQoaAZHQIFpgHJLdvdoB01hAWgIR0C3XnnvUjLTdX2UKGgGR0CKPY4pc5bRaAdNfQJoCEdAt176GZeAu3V9lChoBkdAkxZ0hvBJqmgHTWoDaAhHQLdfWrksBhh1fZQoaAZHQGE5Dg62fChoB0tRaAhHQLdfl987ZFp1fZQoaAZHQI63klu3trtoB03mAmgIR0C3X877oB7vdWUu"
89
+ },
90
+ "ep_success_buffer": {
91
+ ":type:": "<class 'collections.deque'>",
92
+ ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
93
+ },
94
+ "_n_updates": 62500,
95
+ "n_steps": 8,
96
+ "gamma": 0.99,
97
+ "gae_lambda": 0.9,
98
+ "ent_coef": 0.0,
99
+ "vf_coef": 0.4,
100
+ "max_grad_norm": 0.5,
101
+ "normalize_advantage": false,
102
+ "_last_dones": {
103
+ ":type:": "<class 'numpy.ndarray'>",
104
+ ":serialized:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg=="
105
+ }
106
+ }
a2c-HopperBulletEnv-v0/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:eb63027c8c524ae55834326ba3492732346dafcc044f1a8719903f13a581fcf7
3
+ size 47422
a2c-HopperBulletEnv-v0/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5c9c521b9ea562778933b08a8fb1f0ff9a13aeec49a62f53d5cbb702cd2fcb69
3
+ size 48062
a2c-HopperBulletEnv-v0/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-HopperBulletEnv-v0/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid #49~20.04.1-Ubuntu SMP Wed May 18 18:44:28 UTC 2022
2
+ Python: 3.7.10
3
+ Stable-Baselines3: 1.5.1a8
4
+ PyTorch: 1.11.0
5
+ GPU Enabled: True
6
+ Numpy: 1.21.2
7
+ Gym: 0.21.0
args.yml ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - algo
3
+ - a2c
4
+ - - env
5
+ - HopperBulletEnv-v0
6
+ - - env_kwargs
7
+ - null
8
+ - - eval_episodes
9
+ - 10
10
+ - - eval_freq
11
+ - 10000
12
+ - - gym_packages
13
+ - []
14
+ - - hyperparams
15
+ - null
16
+ - - log_folder
17
+ - rl-trained-agents/
18
+ - - log_interval
19
+ - -1
20
+ - - n_evaluations
21
+ - 20
22
+ - - n_jobs
23
+ - 1
24
+ - - n_startup_trials
25
+ - 10
26
+ - - n_timesteps
27
+ - -1
28
+ - - n_trials
29
+ - 10
30
+ - - num_threads
31
+ - -1
32
+ - - optimize_hyperparameters
33
+ - false
34
+ - - pruner
35
+ - median
36
+ - - sampler
37
+ - tpe
38
+ - - save_freq
39
+ - -1
40
+ - - save_replay_buffer
41
+ - false
42
+ - - seed
43
+ - 3332077129
44
+ - - storage
45
+ - null
46
+ - - study_name
47
+ - null
48
+ - - tensorboard_log
49
+ - ''
50
+ - - trained_agent
51
+ - ''
52
+ - - truncate_last_trajectory
53
+ - true
54
+ - - uuid
55
+ - true
56
+ - - vec_env
57
+ - dummy
58
+ - - verbose
59
+ - 1
config.yml ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - ent_coef
3
+ - 0.0
4
+ - - env_wrapper
5
+ - sb3_contrib.common.wrappers.TimeFeatureWrapper
6
+ - - gae_lambda
7
+ - 0.9
8
+ - - gamma
9
+ - 0.99
10
+ - - learning_rate
11
+ - lin_0.00096
12
+ - - max_grad_norm
13
+ - 0.5
14
+ - - n_envs
15
+ - 4
16
+ - - n_steps
17
+ - 8
18
+ - - n_timesteps
19
+ - 2000000.0
20
+ - - normalize
21
+ - true
22
+ - - normalize_advantage
23
+ - false
24
+ - - policy
25
+ - MlpPolicy
26
+ - - policy_kwargs
27
+ - dict(log_std_init=-2, ortho_init=False)
28
+ - - use_rms_prop
29
+ - true
30
+ - - use_sde
31
+ - true
32
+ - - vf_coef
33
+ - 0.4
env_kwargs.yml ADDED
@@ -0,0 +1 @@
 
 
1
+ {}
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5fdd0101e207c517d07c35c922f6524101cdd62e87b5efd1be30db569e6f4a2d
3
+ size 939193
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 709.3425927999999, "std_reward": 213.23864118868931, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T17:27:09.731548"}
train_eval_metrics.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8ff73875cebd26d55f166d3bd4029b54a0620fafe864a7f446dbdef898ed9198
3
+ size 185950
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d19558c9875bbbb2562cdf00bde44d2ec5fe0bd3beb61290a6d89c8d694249f8
3
+ size 4950