Commit
•
43eeb0f
1
Parent(s):
d016f42
Initial commit
Browse files- .gitattributes +1 -0
- README.md +37 -0
- a2c-AntBulletEnv-v0.zip +3 -0
- a2c-AntBulletEnv-v0/_stable_baselines3_version +1 -0
- a2c-AntBulletEnv-v0/data +106 -0
- a2c-AntBulletEnv-v0/policy.optimizer.pth +3 -0
- a2c-AntBulletEnv-v0/policy.pth +3 -0
- a2c-AntBulletEnv-v0/pytorch_variables.pth +3 -0
- a2c-AntBulletEnv-v0/system_info.txt +7 -0
- config.json +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
- vec_normalize.pkl +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 |
+
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 |
+
- AntBulletEnv-v0
|
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: AntBulletEnv-v0
|
16 |
+
type: AntBulletEnv-v0
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 880.95 +/- 540.24
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **A2C** Agent playing **AntBulletEnv-v0**
|
25 |
+
This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
|
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 |
+
```
|
a2c-AntBulletEnv-v0.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b56b4631be600184362c506739c263cbcc0374a6dcd6ff8edd3b4ad9c4abe52e
|
3 |
+
size 129257
|
a2c-AntBulletEnv-v0/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
a2c-AntBulletEnv-v0/data
ADDED
@@ -0,0 +1,106 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f7ac74ae700>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7ac74ae790>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7ac74ae820>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7ac74ae8b0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f7ac74ae940>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f7ac74ae9d0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7ac74aea60>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7ac74aeaf0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f7ac74aeb80>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7ac74aec10>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7ac74aeca0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7ac74aed30>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f7ac74b00c0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {
|
24 |
+
":type:": "<class 'dict'>",
|
25 |
+
":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
|
26 |
+
"log_std_init": -2,
|
27 |
+
"ortho_init": false,
|
28 |
+
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
29 |
+
"optimizer_kwargs": {
|
30 |
+
"alpha": 0.99,
|
31 |
+
"eps": 1e-05,
|
32 |
+
"weight_decay": 0
|
33 |
+
}
|
34 |
+
},
|
35 |
+
"observation_space": {
|
36 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
37 |
+
":serialized:": "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",
|
38 |
+
"dtype": "float32",
|
39 |
+
"_shape": [
|
40 |
+
28
|
41 |
+
],
|
42 |
+
"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]",
|
43 |
+
"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]",
|
44 |
+
"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]",
|
45 |
+
"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]",
|
46 |
+
"_np_random": null
|
47 |
+
},
|
48 |
+
"action_space": {
|
49 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
50 |
+
":serialized:": "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",
|
51 |
+
"dtype": "float32",
|
52 |
+
"_shape": [
|
53 |
+
8
|
54 |
+
],
|
55 |
+
"low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
|
56 |
+
"high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
|
57 |
+
"bounded_below": "[ True True True True True True True True]",
|
58 |
+
"bounded_above": "[ True True True True True True True True]",
|
59 |
+
"_np_random": null
|
60 |
+
},
|
61 |
+
"n_envs": 4,
|
62 |
+
"num_timesteps": 2000000,
|
63 |
+
"_total_timesteps": 2000000,
|
64 |
+
"_num_timesteps_at_start": 0,
|
65 |
+
"seed": null,
|
66 |
+
"action_noise": null,
|
67 |
+
"start_time": 1678804036644883299,
|
68 |
+
"learning_rate": 0.00096,
|
69 |
+
"tensorboard_log": null,
|
70 |
+
"lr_schedule": {
|
71 |
+
":type:": "<class 'function'>",
|
72 |
+
":serialized:": "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"
|
73 |
+
},
|
74 |
+
"_last_obs": {
|
75 |
+
":type:": "<class 'numpy.ndarray'>",
|
76 |
+
":serialized:": "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"
|
77 |
+
},
|
78 |
+
"_last_episode_starts": {
|
79 |
+
":type:": "<class 'numpy.ndarray'>",
|
80 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
81 |
+
},
|
82 |
+
"_last_original_obs": {
|
83 |
+
":type:": "<class 'numpy.ndarray'>",
|
84 |
+
":serialized:": "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"
|
85 |
+
},
|
86 |
+
"_episode_num": 0,
|
87 |
+
"use_sde": true,
|
88 |
+
"sde_sample_freq": -1,
|
89 |
+
"_current_progress_remaining": 0.0,
|
90 |
+
"ep_info_buffer": {
|
91 |
+
":type:": "<class 'collections.deque'>",
|
92 |
+
":serialized:": "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"
|
93 |
+
},
|
94 |
+
"ep_success_buffer": {
|
95 |
+
":type:": "<class 'collections.deque'>",
|
96 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
97 |
+
},
|
98 |
+
"_n_updates": 62500,
|
99 |
+
"n_steps": 8,
|
100 |
+
"gamma": 0.99,
|
101 |
+
"gae_lambda": 0.9,
|
102 |
+
"ent_coef": 0.0,
|
103 |
+
"vf_coef": 0.4,
|
104 |
+
"max_grad_norm": 0.5,
|
105 |
+
"normalize_advantage": false
|
106 |
+
}
|
a2c-AntBulletEnv-v0/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:70bc7f3e1c42d3742f28d191114021c54eecd2ccb4bed4f293871cbcbce9a8b7
|
3 |
+
size 56190
|
a2c-AntBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8ef507e4fe84718e7a6b5403084c3bdc6abbc060b703e55a4e580083b3ff02e5
|
3 |
+
size 56958
|
a2c-AntBulletEnv-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-AntBulletEnv-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.9.16
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|
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 0x7f7ac74ae700>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7ac74ae790>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7ac74ae820>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7ac74ae8b0>", "_build": "<function ActorCriticPolicy._build at 0x7f7ac74ae940>", "forward": "<function ActorCriticPolicy.forward at 0x7f7ac74ae9d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7ac74aea60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7ac74aeaf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7ac74aeb80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7ac74aec10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7ac74aeca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7ac74aed30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f7ac74b00c0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [28], "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]", "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]", "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]", "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]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/AACAvwAAgL8AAIC/AACAv5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAQEBAQEBAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAEBAQEBAQEBlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678804036644883299, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "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": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3c31f4cf426c066bc83adc8ddf1965901daf909722ce7adf95f6b5e99081af3e
|
3 |
+
size 1000346
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 880.9468091679039, "std_reward": 540.2392023666018, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-14T16:11:29.615637"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:64510b54e01ab148bdccab2bb0f349a4ceb0b1afa980aacf48cf44b87e4cd6bb
|
3 |
+
size 2136
|