DQN trained with rl-baselines3-zoo.
Browse files- .gitattributes +1 -0
- DQN-mountaincar-zoo-seed-4128998006.zip +3 -0
- DQN-mountaincar-zoo-seed-4128998006/_stable_baselines3_version +1 -0
- DQN-mountaincar-zoo-seed-4128998006/data +125 -0
- DQN-mountaincar-zoo-seed-4128998006/policy.optimizer.pth +3 -0
- DQN-mountaincar-zoo-seed-4128998006/policy.pth +3 -0
- DQN-mountaincar-zoo-seed-4128998006/pytorch_variables.pth +3 -0
- DQN-mountaincar-zoo-seed-4128998006/system_info.txt +7 -0
- README.md +36 -0
- config.json +1 -0
- results.json +1 -0
.gitattributes
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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DQN-mountaincar-zoo-seed-4128998006.zip
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DQN-mountaincar-zoo-seed-4128998006/data
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"batch_size": 128,
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":type:": "<class 'abc.ABCMeta'>",
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"__module__": "stable_baselines3.common.buffers",
|
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"__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:\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 :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 ",
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"__init__": "<function ReplayBuffer.__init__ at 0x7ff47da5c2f0>",
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},
|
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"replay_buffer_kwargs": {},
|
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"remove_time_limit_termination": false,
|
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"train_freq": {
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":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
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":serialized:": "gASVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLEGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
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},
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"actor": null,
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|
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|
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"exploration_schedule": {
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":type:": "<class 'function'>",
|
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|
124 |
+
}
|
125 |
+
}
|
DQN-mountaincar-zoo-seed-4128998006/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
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oid sha256:a009beec913840b0c87138f6db3a8011fafa7713fa9b722c2792f898602bc62e
|
3 |
+
size 541953
|
DQN-mountaincar-zoo-seed-4128998006/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:dcfe814833ea8b5aa612b57e7df175f7b21adf006cbce8b9fd8f22b71f485d92
|
3 |
+
size 542721
|
DQN-mountaincar-zoo-seed-4128998006/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
DQN-mountaincar-zoo-seed-4128998006/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
OS: Linux-4.15.0-184-generic-x86_64-with-Ubuntu-18.04-bionic #194-Ubuntu SMP Thu Jun 2 18:54:48 UTC 2022
|
2 |
+
Python: 3.6.9
|
3 |
+
Stable-Baselines3: 1.3.0
|
4 |
+
PyTorch: 1.10.2+cu102
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.19.5
|
7 |
+
Gym: 0.19.0
|
README.md
ADDED
@@ -0,0 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- MountainCar-v0
|
5 |
+
- deep-reinforcement-learning
|
6 |
+
- reinforcement-learning
|
7 |
+
- stable-baselines3
|
8 |
+
model-index:
|
9 |
+
- name: DQN
|
10 |
+
results:
|
11 |
+
- metrics:
|
12 |
+
- type: mean_reward
|
13 |
+
value: -104.90 +/- 6.80
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: MountainCar-v0
|
20 |
+
type: MountainCar-v0
|
21 |
+
---
|
22 |
+
|
23 |
+
# **DQN** Agent playing **MountainCar-v0**
|
24 |
+
This is a trained model of a **DQN** agent playing **MountainCar-v0**
|
25 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
26 |
+
|
27 |
+
## Usage (with Stable-baselines3)
|
28 |
+
TODO: Add your code
|
29 |
+
|
30 |
+
|
31 |
+
```python
|
32 |
+
from stable_baselines3 import ...
|
33 |
+
from huggingface_sb3 import load_from_hub
|
34 |
+
|
35 |
+
...
|
36 |
+
```
|
config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__doc__": "\n Policy class with Q-Value Net and target net for DQN\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 ", "__init__": 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results.json
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{"mean_reward": -104.9, "std_reward": 6.80367547726962, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-11T21:55:07.726830"}
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