NielsV commited on
Commit
e62ba0c
·
1 Parent(s): b6e810c

Push agent to the Hub

Browse files
Files changed (3) hide show
  1. README.md +7 -7
  2. replay.mp4 +0 -0
  3. results.json +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
2
  tags:
3
- - CartPole-v1
4
  - ppo
5
  - deep-reinforcement-learning
6
  - reinforcement-learning
@@ -13,18 +13,18 @@ model-index:
13
  type: reinforcement-learning
14
  name: reinforcement-learning
15
  dataset:
16
- name: CartPole-v1
17
- type: CartPole-v1
18
  metrics:
19
  - type: mean_reward
20
- value: -56.94 +/- 54.20
21
  name: mean_reward
22
  verified: false
23
  ---
24
 
25
- # PPO Agent Playing CartPole-v1
26
 
27
- This is a trained model of a PPO agent playing CartPole-v1.
28
 
29
  # Hyperparameters
30
  ```python
@@ -36,7 +36,7 @@ model-index:
36
  'wandb_project_name': 'cleanRL'
37
  'wandb_entity': None
38
  'capture_video': False
39
- 'env_id': 'CartPole-v1'
40
  'total_timesteps': 50000
41
  'learning_rate': 0.00025
42
  'num_envs': 4
 
1
  ---
2
  tags:
3
+ - LunarLander-v2
4
  - ppo
5
  - deep-reinforcement-learning
6
  - reinforcement-learning
 
13
  type: reinforcement-learning
14
  name: reinforcement-learning
15
  dataset:
16
+ name: LunarLander-v2
17
+ type: LunarLander-v2
18
  metrics:
19
  - type: mean_reward
20
+ value: -55.89 +/- 37.85
21
  name: mean_reward
22
  verified: false
23
  ---
24
 
25
+ # PPO Agent Playing LunarLander-v2
26
 
27
+ This is a trained model of a PPO agent playing LunarLander-v2.
28
 
29
  # Hyperparameters
30
  ```python
 
36
  'wandb_project_name': 'cleanRL'
37
  'wandb_entity': None
38
  'capture_video': False
39
+ 'env_id': 'LunarLander-v2'
40
  'total_timesteps': 50000
41
  'learning_rate': 0.00025
42
  'num_envs': 4
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"env_id": "CartPole-v1", "mean_reward": -56.9354474881085, "std_reward": 54.20333751769629, "n_evaluation_episodes": 10, "eval_datetime": "2023-03-13T21:17:19.062586"}
 
1
+ {"env_id": "LunarLander-v2", "mean_reward": -55.89419597242971, "std_reward": 37.845996085227654, "n_evaluation_episodes": 10, "eval_datetime": "2023-03-13T21:17:49.023909"}