Hugging Face's logo

qgallouedec
/
td3-Humanoid-v3-3358106351

Reinforcement Learning
stable-baselines3
Humanoid-v3
deep-reinforcement-learning
Humanoid-v4
Eval Results
Model card Files Community
Quentin Gallouédec commited on
Commit
4b948f7
•
1 Parent(s): 28f288b

Initial commit

Browse files
Files changed (16) hide show
  1. .gitattributes +1 -0
  2. README.md +75 -0
  3. args.yml +83 -0
  4. config.yml +19 -0
  5. env_kwargs.yml +1 -0
  6. replay.mp4 +3 -0
  7. results.json +1 -0
  8. td3-Humanoid-v3.zip +3 -0
  9. td3-Humanoid-v3/_stable_baselines3_version +1 -0
  10. td3-Humanoid-v3/actor.optimizer.pth +3 -0
  11. td3-Humanoid-v3/critic.optimizer.pth +3 -0
  12. td3-Humanoid-v3/data +121 -0
  13. td3-Humanoid-v3/policy.pth +3 -0
  14. td3-Humanoid-v3/pytorch_variables.pth +3 -0
  15. td3-Humanoid-v3/system_info.txt +7 -0
  16. train_eval_metrics.zip +3 -0
.gitattributes CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* 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
 
 
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
35
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - Humanoid-v3
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: TD3
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: Humanoid-v3
16
+ type: Humanoid-v3
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 5397.12 +/- 25.71
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **TD3** Agent playing **Humanoid-v3**
25
+ This is a trained model of a **TD3** agent playing **Humanoid-v3**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
27
+ and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
28
+
29
+ The RL Zoo is a training framework for Stable Baselines3
30
+ reinforcement learning agents,
31
+ with hyperparameter optimization and pre-trained agents included.
32
+
33
+ ## Usage (with SB3 RL Zoo)
34
+
35
+ RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
36
+ SB3: https://github.com/DLR-RM/stable-baselines3<br/>
37
+ SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
38
+
39
+ Install the RL Zoo (with SB3 and SB3-Contrib):
40
+ ```bash
41
+ pip install rl_zoo3
42
+ ```
43
+
44
+ ```
45
+ # Download model and save it into the logs/ folder
46
+ python -m rl_zoo3.load_from_hub --algo td3 --env Humanoid-v3 -orga qgallouedec -f logs/
47
+ python -m rl_zoo3.enjoy --algo td3 --env Humanoid-v3 -f logs/
48
+ ```
49
+
50
+ If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
51
+ ```
52
+ python -m rl_zoo3.load_from_hub --algo td3 --env Humanoid-v3 -orga qgallouedec -f logs/
53
+ python -m rl_zoo3.enjoy --algo td3 --env Humanoid-v3 -f logs/
54
+ ```
55
+
56
+ ## Training (with the RL Zoo)
57
+ ```
58
+ python -m rl_zoo3.train --algo td3 --env Humanoid-v3 -f logs/
59
+ # Upload the model and generate video (when possible)
60
+ python -m rl_zoo3.push_to_hub --algo td3 --env Humanoid-v3 -f logs/ -orga qgallouedec
61
+ ```
62
+
63
+ ## Hyperparameters
64
+ ```python
65
+ OrderedDict([('batch_size', 256),
66
+ ('gradient_steps', 1),
67
+ ('learning_rate', 0.0003),
68
+ ('learning_starts', 10000),
69
+ ('n_timesteps', 2000000.0),
70
+ ('noise_std', 0.1),
71
+ ('noise_type', 'normal'),
72
+ ('policy', 'MlpPolicy'),
73
+ ('train_freq', 1),
74
+ ('normalize', False)])
75
+ ```
args.yml ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - algo
3
+ - td3
4
+ - - conf_file
5
+ - null
6
+ - - device
7
+ - auto
8
+ - - env
9
+ - Humanoid-v3
10
+ - - env_kwargs
11
+ - null
12
+ - - eval_episodes
13
+ - 20
14
+ - - eval_freq
15
+ - 25000
16
+ - - gym_packages
17
+ - []
18
+ - - hyperparams
19
+ - null
20
+ - - log_folder
21
+ - logs
22
+ - - log_interval
23
+ - -1
24
+ - - max_total_trials
25
+ - null
26
+ - - n_eval_envs
27
+ - 5
28
+ - - n_evaluations
29
+ - null
30
+ - - n_jobs
31
+ - 1
32
+ - - n_startup_trials
33
+ - 10
34
+ - - n_timesteps
35
+ - -1
36
+ - - n_trials
37
+ - 500
38
+ - - no_optim_plots
39
+ - false
40
+ - - num_threads
41
+ - -1
42
+ - - optimization_log_path
43
+ - null
44
+ - - optimize_hyperparameters
45
+ - false
46
+ - - progress
47
+ - false
48
+ - - pruner
49
+ - median
50
+ - - sampler
51
+ - tpe
52
+ - - save_freq
53
+ - -1
54
+ - - save_replay_buffer
55
+ - false
56
+ - - seed
57
+ - 3358106351
58
+ - - storage
59
+ - null
60
+ - - study_name
61
+ - null
62
+ - - tensorboard_log
63
+ - runs/Humanoid-v3__td3__3358106351__1676778715
64
+ - - track
65
+ - true
66
+ - - trained_agent
67
+ - ''
68
+ - - truncate_last_trajectory
69
+ - true
70
+ - - uuid
71
+ - false
72
+ - - vec_env
73
+ - dummy
74
+ - - verbose
75
+ - 1
76
+ - - wandb_entity
77
+ - openrlbenchmark
78
+ - - wandb_project_name
79
+ - sb3
80
+ - - wandb_tags
81
+ - []
82
+ - - yaml_file
83
+ - null
config.yml ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - batch_size
3
+ - 256
4
+ - - gradient_steps
5
+ - 1
6
+ - - learning_rate
7
+ - 0.0003
8
+ - - learning_starts
9
+ - 10000
10
+ - - n_timesteps
11
+ - 2000000.0
12
+ - - noise_std
13
+ - 0.1
14
+ - - noise_type
15
+ - normal
16
+ - - policy
17
+ - MlpPolicy
18
+ - - train_freq
19
+ - 1
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 sha256:0f68ce9bed37f9422ea8aa25cf93397cdda8258af53d914516c82b1f8f130470
3
+ size 1199080
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 5397.1195814, "std_reward": 25.70748805865669, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-28T17:39:07.217268"}
td3-Humanoid-v3.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1db257dec1360fe78ce2c5a84ce707ac30771db7d84141d14dae8480b41b0c67
3
+ size 13391005
td3-Humanoid-v3/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.8.0a6
td3-Humanoid-v3/actor.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5409a3a562e884e4beeda106ecdd74537547f306cce1d14ca225927be70d6408
3
+ size 2214575
td3-Humanoid-v3/critic.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9d2ac3e17015546122a53fc3b4bec4f56db3d375e5ed1a83a1220bd9db2b40d0
3
+ size 4460601
td3-Humanoid-v3/data ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.td3.policies",
6
+ "__doc__": "\n Policy class (with both actor and critic) for TD3.\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 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 :param n_critics: Number of critic networks to create.\n :param share_features_extractor: Whether to share or not the features extractor\n between the actor and the critic (this saves computation time)\n ",
7
+ "__init__": "<function TD3Policy.__init__ at 0x7f0855db0af0>",
8
+ "_build": "<function TD3Policy._build at 0x7f0855db0b80>",
9
+ "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7f0855db0c10>",
10
+ "make_actor": "<function TD3Policy.make_actor at 0x7f0855db0ca0>",
11
+ "make_critic": "<function TD3Policy.make_critic at 0x7f0855db0d30>",
12
+ "forward": "<function TD3Policy.forward at 0x7f0855db0dc0>",
13
+ "_predict": "<function TD3Policy._predict at 0x7f0855db0e50>",
14
+ "set_training_mode": "<function TD3Policy.set_training_mode at 0x7f0855db0ee0>",
15
+ "__abstractmethods__": "frozenset()",
16
+ "_abc_impl": "<_abc._abc_data object at 0x7f0855db3940>"
17
+ },
18
+ "verbose": 1,
19
+ "policy_kwargs": {},
20
+ "observation_space": {
21
+ ":type:": "<class 'gym.spaces.box.Box'>",
22
+ ":serialized:": "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",
23
+ "dtype": "float64",
24
+ "_shape": [
25
+ 376
26
+ ],
27
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
28
+ "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]",
29
+ "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
30
+ "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
31
+ "_np_random": null
32
+ },
33
+ "action_space": {
34
+ ":type:": "<class 'gym.spaces.box.Box'>",
35
+ ":serialized:": "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",
36
+ "dtype": "float32",
37
+ "_shape": [
38
+ 17
39
+ ],
40
+ "low": "[-0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4\n -0.4 -0.4 -0.4]",
41
+ "high": "[0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4]",
42
+ "bounded_below": "[ True True True True True True True True True True True True\n True True True True True]",
43
+ "bounded_above": "[ True True True True True True True True True True True True\n True True True True True]",
44
+ "_np_random": "RandomState(MT19937)"
45
+ },
46
+ "n_envs": 1,
47
+ "num_timesteps": 2000000,
48
+ "_total_timesteps": 2000000,
49
+ "_num_timesteps_at_start": 0,
50
+ "seed": 0,
51
+ "action_noise": {
52
+ ":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>",
53
+ ":serialized:": "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",
54
+ "_mu": "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]",
55
+ "_sigma": "[0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]"
56
+ },
57
+ "start_time": 1676778718772608094,
58
+ "learning_rate": {
59
+ ":type:": "<class 'function'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "tensorboard_log": "runs/Humanoid-v3__td3__3358106351__1676778715/Humanoid-v3",
63
+ "lr_schedule": {
64
+ ":type:": "<class 'function'>",
65
+ ":serialized:": "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"
66
+ },
67
+ "_last_obs": null,
68
+ "_last_episode_starts": {
69
+ ":type:": "<class 'numpy.ndarray'>",
70
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
71
+ },
72
+ "_last_original_obs": {
73
+ ":type:": "<class 'numpy.ndarray'>",
74
+ ":serialized:": "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"
75
+ },
76
+ "_episode_num": 6747,
77
+ "use_sde": false,
78
+ "sde_sample_freq": -1,
79
+ "_current_progress_remaining": 0.0,
80
+ "ep_info_buffer": {
81
+ ":type:": "<class 'collections.deque'>",
82
+ ":serialized:": "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"
83
+ },
84
+ "ep_success_buffer": {
85
+ ":type:": "<class 'collections.deque'>",
86
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
87
+ },
88
+ "_n_updates": 1990000,
89
+ "buffer_size": 1,
90
+ "batch_size": 256,
91
+ "learning_starts": 10000,
92
+ "tau": 0.005,
93
+ "gamma": 0.99,
94
+ "gradient_steps": 1,
95
+ "optimize_memory_usage": false,
96
+ "replay_buffer_class": {
97
+ ":type:": "<class 'abc.ABCMeta'>",
98
+ ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
99
+ "__module__": "stable_baselines3.common.buffers",
100
+ "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ",
101
+ "__init__": "<function ReplayBuffer.__init__ at 0x7f0855dae5e0>",
102
+ "add": "<function ReplayBuffer.add at 0x7f0855dae670>",
103
+ "sample": "<function ReplayBuffer.sample at 0x7f0855dae700>",
104
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7f0855dae790>",
105
+ "__abstractmethods__": "frozenset()",
106
+ "_abc_impl": "<_abc._abc_data object at 0x7f0855da6840>"
107
+ },
108
+ "replay_buffer_kwargs": {},
109
+ "train_freq": {
110
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
111
+ ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
112
+ },
113
+ "use_sde_at_warmup": false,
114
+ "policy_delay": 2,
115
+ "target_noise_clip": 0.5,
116
+ "target_policy_noise": 0.2,
117
+ "actor_batch_norm_stats": [],
118
+ "critic_batch_norm_stats": [],
119
+ "actor_batch_norm_stats_target": [],
120
+ "critic_batch_norm_stats_target": []
121
+ }
td3-Humanoid-v3/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f4d5093f29ca592ea75f2b0297048c3506c2dddc3c1f577b03ac8aca62e58cbd
3
+ size 6673017
td3-Humanoid-v3/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
td3-Humanoid-v3/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.19.0-32-generic-x86_64-with-glibc2.35 # 33~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Jan 30 17:03:34 UTC 2
2
+ - Python: 3.9.12
3
+ - Stable-Baselines3: 1.8.0a6
4
+ - PyTorch: 1.13.1+cu117
5
+ - GPU Enabled: True
6
+ - Numpy: 1.24.1
7
+ - Gym: 0.21.0
train_eval_metrics.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a884f1fc8b79314e0c0490382ec6a5ce9ef2cf5691bfb8f5901a174f7fff2b39
3
+ size 209171