Hugging Face's logo

sb3
/
ppo-BipedalWalker-v3

Reinforcement Learning
stable-baselines3
BipedalWalker-v3
deep-reinforcement-learning
Eval Results
Model card Files Community
araffin commited on
Commit
8e927a4
·
1 Parent(s): b462163

Initial commit

Browse files
Files changed (12) hide show
  1. README.md +6 -6
  2. args.yml +29 -9
  3. config.yml +5 -5
  4. ppo-BipedalWalker-v3.zip +2 -2
  5. ppo-BipedalWalker-v3/data +40 -41
  6. ppo-BipedalWalker-v3/policy.optimizer.pth +2 -2
  7. ppo-BipedalWalker-v3/policy.pth +2 -2
  8. ppo-BipedalWalker-v3/system_info.txt +1 -1
  9. replay.mp4 +2 -2
  10. results.json +1 -1
  11. train_eval_metrics.zip +2 -2
  12. vec_normalize.pkl +2 -2
README.md CHANGED
@@ -10,7 +10,7 @@ model-index:
10
  results:
11
  - metrics:
12
  - type: mean_reward
13
- value: 149.15 +/- 162.01
14
  name: mean_reward
15
  task:
16
  type: reinforcement-learning
@@ -51,12 +51,12 @@ python -m utils.push_to_hub --algo ppo --env BipedalWalker-v3 -f logs/ -orga sb3
51
  ## Hyperparameters
52
  ```python
53
  OrderedDict([('batch_size', 64),
54
- ('clip_range', 0.2),
55
- ('ent_coef', 0.001),
56
  ('gae_lambda', 0.95),
57
- ('gamma', 0.99),
58
- ('learning_rate', 0.00025),
59
- ('n_envs', 16),
60
  ('n_epochs', 10),
61
  ('n_steps', 2048),
62
  ('n_timesteps', 5000000.0),
 
10
  results:
11
  - metrics:
12
  - type: mean_reward
13
+ value: 288.30 +/- 2.23
14
  name: mean_reward
15
  task:
16
  type: reinforcement-learning
 
51
  ## Hyperparameters
52
  ```python
53
  OrderedDict([('batch_size', 64),
54
+ ('clip_range', 0.18),
55
+ ('ent_coef', 0.0),
56
  ('gae_lambda', 0.95),
57
+ ('gamma', 0.999),
58
+ ('learning_rate', 0.0003),
59
+ ('n_envs', 32),
60
  ('n_epochs', 10),
61
  ('n_steps', 2048),
62
  ('n_timesteps', 5000000.0),
args.yml CHANGED
@@ -1,24 +1,34 @@
1
  !!python/object/apply:collections.OrderedDict
2
  - - - algo
3
  - ppo
 
 
4
  - - env
5
  - BipedalWalker-v3
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
@@ -26,9 +36,13 @@
26
  - - n_timesteps
27
  - -1
28
  - - n_trials
29
- - 10
 
 
30
  - - num_threads
31
  - -1
 
 
32
  - - optimize_hyperparameters
33
  - false
34
  - - pruner
@@ -40,20 +54,26 @@
40
  - - save_replay_buffer
41
  - false
42
  - - seed
43
- - 2229112069
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
 
 
 
 
 
1
  !!python/object/apply:collections.OrderedDict
2
  - - - algo
3
  - ppo
4
+ - - device
5
+ - auto
6
  - - env
7
  - BipedalWalker-v3
8
  - - env_kwargs
9
  - null
10
  - - eval_episodes
11
+ - 5
12
  - - eval_freq
13
+ - 25000
14
  - - gym_packages
15
  - []
16
  - - hyperparams
17
+ - clip_range: 0.18
18
+ ent_coef: 0.0
19
+ gamma: 0.999
20
+ learning_rate: 0.0003
21
+ n_envs: 32
22
  - - log_folder
23
+ - logs/
24
  - - log_interval
25
  - -1
26
+ - - max_total_trials
27
+ - null
28
+ - - n_eval_envs
29
+ - 1
30
  - - n_evaluations
31
+ - null
32
  - - n_jobs
33
  - 1
34
  - - n_startup_trials
 
36
  - - n_timesteps
37
  - -1
38
  - - n_trials
39
+ - 500
40
+ - - no_optim_plots
41
+ - false
42
  - - num_threads
43
  - -1
44
+ - - optimization_log_path
45
+ - null
46
  - - optimize_hyperparameters
47
  - false
48
  - - pruner
 
54
  - - save_replay_buffer
55
  - false
56
  - - seed
57
+ - 901494559
58
  - - storage
59
  - null
60
  - - study_name
61
  - null
62
  - - tensorboard_log
63
+ - runs/BipedalWalker-v3__ppo__901494559__1654177177
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
config.yml CHANGED
@@ -2,17 +2,17 @@
2
  - - - batch_size
3
  - 64
4
  - - clip_range
5
- - 0.2
6
  - - ent_coef
7
- - 0.001
8
  - - gae_lambda
9
  - 0.95
10
  - - gamma
11
- - 0.99
12
  - - learning_rate
13
- - 0.00025
14
  - - n_envs
15
- - 16
16
  - - n_epochs
17
  - 10
18
  - - n_steps
 
2
  - - - batch_size
3
  - 64
4
  - - clip_range
5
+ - 0.18
6
  - - ent_coef
7
+ - 0.0
8
  - - gae_lambda
9
  - 0.95
10
  - - gamma
11
+ - 0.999
12
  - - learning_rate
13
+ - 0.0003
14
  - - n_envs
15
+ - 32
16
  - - n_epochs
17
  - 10
18
  - - n_steps
ppo-BipedalWalker-v3.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:112e474c550acc9c072def4f8652a43993ba17fc957c8286f8e1201ca8529ff7
3
- size 176956
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:754a31f681a7436229fd1fea4aa0fc47f974b847dd214e13145c6fec3c895a09
3
+ size 178617
ppo-BipedalWalker-v3/data CHANGED
@@ -4,100 +4,99 @@
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 0x7fd716bd9950>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd716bd99e0>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd716bd9a70>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd716bd9b00>",
11
- "_build": "<function ActorCriticPolicy._build at 0x7fd716bd9b90>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x7fd716bd9c20>",
13
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd716bd9cb0>",
14
- "_predict": "<function ActorCriticPolicy._predict at 0x7fd716bd9d40>",
15
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd716bd9dd0>",
16
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd716bd9e60>",
17
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd716bd9ef0>",
18
  "__abstractmethods__": "frozenset()",
19
- "_abc_impl": "<_abc_data object at 0x7fd716c2a840>"
20
  },
21
  "verbose": 1,
22
  "policy_kwargs": {},
23
  "observation_space": {
24
  ":type:": "<class 'gym.spaces.box.Box'>",
25
- ":serialized:": "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",
26
  "dtype": "float32",
 
 
 
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]",
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]",
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]",
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]",
31
- "_np_random": null,
32
- "_shape": [
33
- 24
34
- ]
35
  },
36
  "action_space": {
37
  ":type:": "<class 'gym.spaces.box.Box'>",
38
- ":serialized:": "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",
39
  "dtype": "float32",
 
 
 
40
  "low": "[-1. -1. -1. -1.]",
41
  "high": "[1. 1. 1. 1.]",
42
  "bounded_below": "[ True True True True]",
43
  "bounded_above": "[ True True True True]",
44
- "_np_random": "RandomState(MT19937)",
45
- "_shape": [
46
- 4
47
- ]
48
  },
49
- "n_envs": 16,
50
- "num_timesteps": 5013504,
51
  "_total_timesteps": 5000000,
52
  "_num_timesteps_at_start": 0,
53
  "seed": 0,
54
  "action_noise": null,
55
- "start_time": 1614710447.1098251,
56
  "learning_rate": {
57
  ":type:": "<class 'function'>",
58
- ":serialized:": "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"
59
  },
60
- "tensorboard_log": null,
61
  "lr_schedule": {
62
  ":type:": "<class 'function'>",
63
- ":serialized:": "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"
64
  },
65
  "_last_obs": null,
66
- "_last_episode_starts": null,
 
 
 
67
  "_last_original_obs": {
68
  ":type:": "<class 'numpy.ndarray'>",
69
- ":serialized:": "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"
70
  },
71
  "_episode_num": 0,
72
  "use_sde": false,
73
  "sde_sample_freq": -1,
74
- "_current_progress_remaining": -0.0027007999999999477,
75
  "ep_info_buffer": {
76
  ":type:": "<class 'collections.deque'>",
77
- ":serialized:": "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"
78
  },
79
  "ep_success_buffer": {
80
  ":type:": "<class 'collections.deque'>",
81
  ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
82
  },
83
- "_n_updates": 1530,
84
  "n_steps": 2048,
85
- "gamma": 0.99,
86
  "gae_lambda": 0.95,
87
- "ent_coef": 0.001,
88
  "vf_coef": 0.5,
89
  "max_grad_norm": 0.5,
90
  "batch_size": 64,
91
  "n_epochs": 10,
92
  "clip_range": {
93
  ":type:": "<class 'function'>",
94
- ":serialized:": "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"
95
  },
96
  "clip_range_vf": null,
97
  "normalize_advantage": true,
98
- "target_kl": null,
99
- "_last_dones": {
100
- ":type:": "<class 'numpy.ndarray'>",
101
- ":serialized:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
102
- }
103
  }
 
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 0x7fccc6e3f950>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fccc6e3f9e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fccc6e3fa70>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fccc6e3fb00>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fccc6e3fb90>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fccc6e3fc20>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fccc6e3fcb0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fccc6e3fd40>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fccc6e3fdd0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fccc6e3fe60>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fccc6e3fef0>",
18
  "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fccc6e91810>"
20
  },
21
  "verbose": 1,
22
  "policy_kwargs": {},
23
  "observation_space": {
24
  ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
  "dtype": "float32",
27
+ "_shape": [
28
+ 24
29
+ ],
30
  "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]",
31
  "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]",
32
  "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]",
33
  "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]",
34
+ "_np_random": null
 
 
 
35
  },
36
  "action_space": {
37
  ":type:": "<class 'gym.spaces.box.Box'>",
38
+ ":serialized:": "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",
39
  "dtype": "float32",
40
+ "_shape": [
41
+ 4
42
+ ],
43
  "low": "[-1. -1. -1. -1.]",
44
  "high": "[1. 1. 1. 1.]",
45
  "bounded_below": "[ True True True True]",
46
  "bounded_above": "[ True True True True]",
47
+ "_np_random": "RandomState(MT19937)"
 
 
 
48
  },
49
+ "n_envs": 32,
50
+ "num_timesteps": 5046272,
51
  "_total_timesteps": 5000000,
52
  "_num_timesteps_at_start": 0,
53
  "seed": 0,
54
  "action_noise": null,
55
+ "start_time": 1654177183.9184453,
56
  "learning_rate": {
57
  ":type:": "<class 'function'>",
58
+ ":serialized:": "gASVywIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxOL2hvbWUvYW50b25pbi9Eb2N1bWVudHMvcmwvc3RhYmxlLWJhc2VsaW5lczMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxOL2hvbWUvYW50b25pbi9Eb2N1bWVudHMvcmwvc3RhYmxlLWJhc2VsaW5lczMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
59
  },
60
+ "tensorboard_log": "runs/BipedalWalker-v3__ppo__901494559__1654177177/BipedalWalker-v3",
61
  "lr_schedule": {
62
  ":type:": "<class 'function'>",
63
+ ":serialized:": "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"
64
  },
65
  "_last_obs": null,
66
+ "_last_episode_starts": {
67
+ ":type:": "<class 'numpy.ndarray'>",
68
+ ":serialized:": "gASVqAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSyCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlHSUYi4="
69
+ },
70
  "_last_original_obs": {
71
  ":type:": "<class 'numpy.ndarray'>",
72
+ ":serialized:": "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"
73
  },
74
  "_episode_num": 0,
75
  "use_sde": false,
76
  "sde_sample_freq": -1,
77
+ "_current_progress_remaining": -0.009254400000000107,
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
  },
86
+ "_n_updates": 770,
87
  "n_steps": 2048,
88
+ "gamma": 0.999,
89
  "gae_lambda": 0.95,
90
+ "ent_coef": 0.0,
91
  "vf_coef": 0.5,
92
  "max_grad_norm": 0.5,
93
  "batch_size": 64,
94
  "n_epochs": 10,
95
  "clip_range": {
96
  ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
  },
99
  "clip_range_vf": null,
100
  "normalize_advantage": true,
101
+ "target_kl": null
 
 
 
 
102
  }
ppo-BipedalWalker-v3/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e31e80379cc6dd8f604ba6227b3c22ca90efcff8a29474b6c453861f798c7fe9
3
- size 101783
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c5f80dfaab562a595c3a1c83c91c241c78321c998ef8c501f759fa43745da317
3
+ size 101527
ppo-BipedalWalker-v3/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ddeb45f67b5672ef5977fd26d3620c259482f5e2b94fd06716eacecca1cffe08
3
- size 51710
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d825cccdc23817c575b036b09ad88bb3105f128e5dace397a738d06df2e7e3c4
3
+ size 51582
ppo-BipedalWalker-v3/system_info.txt CHANGED
@@ -2,6 +2,6 @@ OS: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid #49~20.04.1-Ubuntu S
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
 
2
  Python: 3.7.10
3
  Stable-Baselines3: 1.5.1a8
4
  PyTorch: 1.11.0
5
+ GPU Enabled: False
6
  Numpy: 1.21.2
7
  Gym: 0.21.0
replay.mp4 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:4fceab4205294d39eac76ba9ad00897505f87598a63d5d78680e43bb0d017377
3
- size 450631
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a6e3aeef535b0374633d9352accabc22a5997b85a3c740dc8cefc114e8dfa284
3
+ size 470021
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 149.1450564, "std_reward": 162.00872673242017, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T14:26:00.960674"}
 
1
+ {"mean_reward": 288.29576269999995, "std_reward": 2.230729416083094, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T16:39:48.338426"}
train_eval_metrics.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ed14a798f3e8d2d8b03e7ee6ebac82272cf124c38bf0939732e73ea7603da6e0
3
- size 229035
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca925e4485bbd636449ace1c1a12c37a34c49c5a2a6675643b0ecdbb8dc75f27
3
+ size 130764
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:818cb2ae0db16c862d0f1a414ee304004e48331bc45b80dfe7d852ace20527f7
3
- size 6496
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:376e43c4a4436583cb38ce71987030b213a04fe0c9c1c1a934b96f4fb28d4cf0
3
+ size 8101