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Initial commit of Pyramids training results

Browse files
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+ default_settings: null
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+ behaviors:
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+ Pyramids:
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+ trainer_type: ppo
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+ hyperparameters:
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+ batch_size: 128
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+ buffer_size: 2048
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+ learning_rate: 0.0003
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+ beta: 0.01
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+ num_layers: 2
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+ vis_encode_type: simple
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+ memory: null
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+ goal_conditioning_type: hyper
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+ num_layers: 3
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+ learning_rate: 0.0001
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+ height: 84
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+ run_id: Pyramids Training
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+ load_model: false
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+ results_dir: ./results
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README.md ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: ml-agents
3
+ tags:
4
+ - Pyramids
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - ML-Agents-Pyramids
8
+ ---
9
+
10
+ # **ppo** Agent playing **Pyramids**
11
+ This is a trained model of a **ppo** agent playing **Pyramids**
12
+ using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
13
+
14
+ ## Usage (with ML-Agents)
15
+ The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
16
+
17
+ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
18
+ - A *short tutorial* where you teach Huggy the Dog 🐢 to fetch the stick and then play with him directly in your
19
+ browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
20
+ - A *longer tutorial* to understand how works ML-Agents:
21
+ https://huggingface.co/learn/deep-rl-course/unit5/introduction
22
+
23
+ ### Resume the training
24
+ ```bash
25
+ mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
26
+ ```
27
+
28
+ ### Watch your Agent play
29
+ You can watch your agent **playing directly in your browser**
30
+
31
+ 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
32
+ 2. Step 1: Find your model_id: alidenewade/ML-Agents-Pyramids
33
+ 3. Step 2: Select your *.nn /*.onnx file
34
+ 4. Click on Watch the agent play πŸ‘€
35
+
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"behaviors": {"Pyramids": {"trainer_type": "ppo", "hyperparameters": {"batch_size": 128, "buffer_size": 2048, "learning_rate": 0.0003, "beta": 0.01, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 3, "learning_rate_schedule": "linear"}, "network_settings": {"normalize": false, "hidden_units": 512, "num_layers": 2, "vis_encode_type": "simple"}, "reward_signals": {"extrinsic": {"gamma": 0.99, "strength": 1.0}, "rnd": {"gamma": 0.99, "strength": 0.01, "network_settings": {"hidden_units": 64, "num_layers": 3}, "learning_rate": 0.0001}}, "keep_checkpoints": 5, "max_steps": 1500000, "time_horizon": 128, "summary_freq": 30000}}}
configuration.yaml ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ behaviors:
2
+ Pyramids:
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+ trainer_type: ppo
4
+ hyperparameters:
5
+ batch_size: 128
6
+ buffer_size: 2048
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+ learning_rate: 0.0003
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+ beta: 0.01
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+ epsilon: 0.2
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+ lambd: 0.95
11
+ num_epoch: 3
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+ learning_rate_schedule: linear
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+ network_settings:
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+ normalize: false
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+ hidden_units: 512
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+ num_layers: 2
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+ vis_encode_type: simple
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+ reward_signals:
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+ extrinsic:
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+ gamma: 0.99
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+ strength: 1.0
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+ rnd:
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+ gamma: 0.99
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+ strength: 0.01
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+ network_settings:
26
+ hidden_units: 64
27
+ num_layers: 3
28
+ learning_rate: 0.0001
29
+ keep_checkpoints: 5
30
+ max_steps: 1500000
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+ time_horizon: 128
32
+ summary_freq: 30000
mlagents_output.log ADDED
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+
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+ ┐ β•–
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+ ╓╖╬│║ ││╬╖╖
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+ β•“β•–β•¬β”‚β”‚β”‚β”‚β”‚β”˜ ╬│││││╬╖
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+ β•–β•¬β”‚β”‚β”‚β”‚β”‚β•¬β•œ ╙╬│││││╖╖ β•—β•—β•—
6
+ ╬╬╬╬╖││╦╖ ╖╬││╗╣╣╣╬ β•Ÿβ•£β•£β•¬ β•Ÿβ•£β•£β•£ β•œβ•œβ•œ β•Ÿβ•£β•£
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+ ╬╬╬╬╬╬╬╬╖│╬╖╖╓╬β•ͺ│╓╣╣╣╣╣╣╣╬ β•Ÿβ•£β•£β•¬ β•Ÿβ•£β•£β•£ β•’β•£β•£β•–β•—β•£β•£β•£β•— β•£β•£β•£ β•£β•£β•£β•£β•£β•£ β•Ÿβ•£β•£β•– β•£β•£β•£
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+ ╬╬╬╬┐ β•™β•¬β•¬β•¬β•¬β”‚β•“β•£β•£β•£β•β•œ ╫╣╣╣╬ β•Ÿβ•£β•£β•¬ β•Ÿβ•£β•£β•£ β•Ÿβ•£β•£β•£β•™ β•™β•£β•£β•£ β•£β•£β•£ β•™β•Ÿβ•£β•£β•œβ•™ β•«β•£β•£ β•Ÿβ•£β•£
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+ ╬╬╬╬┐ ╙╬╬╣╣ ╫╣╣╣╬ β•Ÿβ•£β•£β•¬ β•Ÿβ•£β•£β•£ β•Ÿβ•£β•£β•¬ β•£β•£β•£ β•£β•£β•£ β•Ÿβ•£β•£ β•£β•£β•£β”Œβ•£β•£β•œ
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+ β•¬β•¬β•¬β•œ ╬╬╣╣ ╙╝╣╣╬ β•™β•£β•£β•£β•—β•–β•“β•—β•£β•£β•£β•œ β•Ÿβ•£β•£β•¬ β•£β•£β•£ β•£β•£β•£ β•Ÿβ•£β•£β•¦β•“ β•£β•£β•£β•£β•£
11
+ β•™ ╓╦╖ ╬╬╣╣ β•“β•—β•—β•– β•™β•β•£β•£β•£β•£β•β•œ β•˜β•β•β•œ ╝╝╝ ╝╝╝ β•™β•£β•£β•£ β•Ÿβ•£β•£β•£
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+ ╩╬╬╬╬╬╬╦╦╬╬╣╣╗╣╣╣╣╣╣╣╝ β•«β•£β•£β•£β•£
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+ β•™β•¬β•¬β•¬β•¬β•¬β•¬β•¬β•£β•£β•£β•£β•£β•£β•β•œ
14
+ β•™β•¬β•¬β•¬β•£β•£β•£β•œ
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+ β•™
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+
17
+ Version information:
18
+ ml-agents: 1.1.0,
19
+ ml-agents-envs: 1.1.0,
20
+ Communicator API: 1.5.0,
21
+ PyTorch: 2.5.1+cu124
22
+ [INFO] Connected to Unity environment with package version 2.2.1-exp.1 and communication version 1.5.0
23
+ [INFO] Connected new brain: Pyramids?team=0
24
+ [INFO] Hyperparameters for behavior name Pyramids:
25
+ trainer_type: ppo
26
+ hyperparameters:
27
+ batch_size: 128
28
+ buffer_size: 2048
29
+ learning_rate: 0.0003
30
+ beta: 0.01
31
+ epsilon: 0.2
32
+ lambd: 0.95
33
+ num_epoch: 3
34
+ shared_critic: False
35
+ learning_rate_schedule: linear
36
+ beta_schedule: linear
37
+ epsilon_schedule: linear
38
+ checkpoint_interval: 500000
39
+ network_settings:
40
+ normalize: False
41
+ hidden_units: 512
42
+ num_layers: 2
43
+ vis_encode_type: simple
44
+ memory: None
45
+ goal_conditioning_type: hyper
46
+ deterministic: False
47
+ reward_signals:
48
+ extrinsic:
49
+ gamma: 0.99
50
+ strength: 1.0
51
+ network_settings:
52
+ normalize: False
53
+ hidden_units: 128
54
+ num_layers: 2
55
+ vis_encode_type: simple
56
+ memory: None
57
+ goal_conditioning_type: hyper
58
+ deterministic: False
59
+ rnd:
60
+ gamma: 0.99
61
+ strength: 0.01
62
+ network_settings:
63
+ normalize: False
64
+ hidden_units: 64
65
+ num_layers: 3
66
+ vis_encode_type: simple
67
+ memory: None
68
+ goal_conditioning_type: hyper
69
+ deterministic: False
70
+ learning_rate: 0.0001
71
+ encoding_size: None
72
+ init_path: None
73
+ keep_checkpoints: 5
74
+ even_checkpoints: False
75
+ max_steps: 1500000
76
+ time_horizon: 128
77
+ summary_freq: 30000
78
+ threaded: False
79
+ self_play: None
80
+ behavioral_cloning: None
81
+ [INFO] Pyramids. Step: 30000. Time Elapsed: 148.003 s. Mean Reward: -1.000. Std of Reward: 0.000. Training.
82
+ [INFO] Pyramids. Step: 60000. Time Elapsed: 265.467 s. Mean Reward: -0.933. Std of Reward: 0.372. Training.
83
+ [INFO] Pyramids. Step: 90000. Time Elapsed: 367.221 s. Mean Reward: -0.710. Std of Reward: 0.798. Training.
84
+ [INFO] Pyramids. Step: 120000. Time Elapsed: 464.638 s. Mean Reward: -0.776. Std of Reward: 0.720. Training.
85
+ [INFO] Pyramids. Step: 150000. Time Elapsed: 558.278 s. Mean Reward: -0.767. Std of Reward: 0.704. Training.
86
+ [INFO] Pyramids. Step: 180000. Time Elapsed: 647.350 s. Mean Reward: -0.735. Std of Reward: 0.702. Training.
87
+ [INFO] Pyramids. Step: 210000. Time Elapsed: 729.384 s. Mean Reward: -0.734. Std of Reward: 0.718. Training.
88
+ [INFO] Pyramids. Step: 240000. Time Elapsed: 811.080 s. Mean Reward: -0.770. Std of Reward: 0.717. Training.
89
+ [INFO] Pyramids. Step: 270000. Time Elapsed: 892.234 s. Mean Reward: -0.677. Std of Reward: 0.828. Training.
90
+ [INFO] Pyramids. Step: 300000. Time Elapsed: 972.033 s. Mean Reward: -0.623. Std of Reward: 0.880. Training.
91
+ [INFO] Pyramids. Step: 330000. Time Elapsed: 1052.993 s. Mean Reward: -0.547. Std of Reward: 0.933. Training.
92
+ [INFO] Pyramids. Step: 360000. Time Elapsed: 1133.943 s. Mean Reward: -0.255. Std of Reward: 1.081. Training.
93
+ [INFO] Pyramids. Step: 390000. Time Elapsed: 1214.047 s. Mean Reward: 0.361. Std of Reward: 1.218. Training.
94
+ [INFO] Pyramids. Step: 420000. Time Elapsed: 1295.921 s. Mean Reward: 0.438. Std of Reward: 1.226. Training.
95
+ [INFO] Pyramids. Step: 450000. Time Elapsed: 1379.688 s. Mean Reward: 0.412. Std of Reward: 1.220. Training.
96
+ [INFO] Pyramids. Step: 480000. Time Elapsed: 1462.029 s. Mean Reward: 0.791. Std of Reward: 1.133. Training.
97
+ [INFO] Exported ./results/Pyramids Training/Pyramids/Pyramids-499993.onnx
98
+ [INFO] Pyramids. Step: 510000. Time Elapsed: 1548.600 s. Mean Reward: 1.152. Std of Reward: 0.981. Training.
99
+ [INFO] Pyramids. Step: 540000. Time Elapsed: 1633.251 s. Mean Reward: 1.311. Std of Reward: 0.824. Training.
100
+ [INFO] Pyramids. Step: 570000. Time Elapsed: 1721.782 s. Mean Reward: 1.343. Std of Reward: 0.833. Training.
101
+ [INFO] Pyramids. Step: 600000. Time Elapsed: 1805.904 s. Mean Reward: 1.378. Std of Reward: 0.772. Training.
102
+ [INFO] Pyramids. Step: 630000. Time Elapsed: 1893.478 s. Mean Reward: 1.566. Std of Reward: 0.591. Training.
103
+ [INFO] Pyramids. Step: 660000. Time Elapsed: 1977.764 s. Mean Reward: 1.453. Std of Reward: 0.686. Training.
104
+ [INFO] Pyramids. Step: 690000. Time Elapsed: 2066.482 s. Mean Reward: 1.632. Std of Reward: 0.319. Training.
105
+ [INFO] Pyramids. Step: 720000. Time Elapsed: 2151.482 s. Mean Reward: 1.549. Std of Reward: 0.660. Training.
106
+ [INFO] Pyramids. Step: 750000. Time Elapsed: 2240.531 s. Mean Reward: 1.592. Std of Reward: 0.536. Training.
107
+ [INFO] Pyramids. Step: 780000. Time Elapsed: 2328.085 s. Mean Reward: 1.706. Std of Reward: 0.193. Training.
108
+ [INFO] Pyramids. Step: 810000. Time Elapsed: 2411.292 s. Mean Reward: 1.578. Std of Reward: 0.580. Training.
109
+ [INFO] Pyramids. Step: 840000. Time Elapsed: 2501.359 s. Mean Reward: 1.682. Std of Reward: 0.335. Training.
110
+ [INFO] Pyramids. Step: 870000. Time Elapsed: 2586.919 s. Mean Reward: 1.659. Std of Reward: 0.333. Training.
111
+ [INFO] Pyramids. Step: 900000. Time Elapsed: 2680.870 s. Mean Reward: 1.629. Std of Reward: 0.434. Training.
112
+ [INFO] Pyramids. Step: 930000. Time Elapsed: 2767.200 s. Mean Reward: 1.597. Std of Reward: 0.560. Training.
113
+ [INFO] Pyramids. Step: 960000. Time Elapsed: 2857.335 s. Mean Reward: 1.724. Std of Reward: 0.166. Training.
114
+ [INFO] Pyramids. Step: 990000. Time Elapsed: 2941.618 s. Mean Reward: 1.619. Std of Reward: 0.553. Training.
115
+ [INFO] Exported ./results/Pyramids Training/Pyramids/Pyramids-999946.onnx
116
+ [INFO] Pyramids. Step: 1020000. Time Elapsed: 3028.674 s. Mean Reward: 1.678. Std of Reward: 0.411. Training.
117
+ [INFO] Pyramids. Step: 1050000. Time Elapsed: 3118.122 s. Mean Reward: 1.692. Std of Reward: 0.402. Training.
118
+ [INFO] Pyramids. Step: 1080000. Time Elapsed: 3216.680 s. Mean Reward: 1.727. Std of Reward: 0.183. Training.
119
+ [INFO] Pyramids. Step: 1110000. Time Elapsed: 3311.014 s. Mean Reward: 1.661. Std of Reward: 0.489. Training.
120
+ [INFO] Pyramids. Step: 1140000. Time Elapsed: 3403.759 s. Mean Reward: 1.660. Std of Reward: 0.528. Training.
121
+ [INFO] Pyramids. Step: 1170000. Time Elapsed: 3502.028 s. Mean Reward: 1.663. Std of Reward: 0.472. Training.
122
+ [INFO] Pyramids. Step: 1200000. Time Elapsed: 3593.599 s. Mean Reward: 1.724. Std of Reward: 0.368. Training.
123
+ [INFO] Pyramids. Step: 1230000. Time Elapsed: 3696.908 s. Mean Reward: 1.726. Std of Reward: 0.294. Training.
124
+ [INFO] Pyramids. Step: 1260000. Time Elapsed: 3794.103 s. Mean Reward: 1.698. Std of Reward: 0.393. Training.
125
+ [INFO] Pyramids. Step: 1290000. Time Elapsed: 3880.079 s. Mean Reward: 1.725. Std of Reward: 0.296. Training.
126
+ [INFO] Pyramids. Step: 1320000. Time Elapsed: 3962.680 s. Mean Reward: 1.721. Std of Reward: 0.297. Training.
127
+ [INFO] Pyramids. Step: 1350000. Time Elapsed: 4045.175 s. Mean Reward: 1.770. Std of Reward: 0.140. Training.
128
+ [INFO] Pyramids. Step: 1380000. Time Elapsed: 4137.379 s. Mean Reward: 1.735. Std of Reward: 0.287. Training.
129
+ [INFO] Pyramids. Step: 1410000. Time Elapsed: 4225.323 s. Mean Reward: 1.680. Std of Reward: 0.395. Training.
130
+ [INFO] Pyramids. Step: 1440000. Time Elapsed: 4312.635 s. Mean Reward: 1.731. Std of Reward: 0.297. Training.
131
+ [INFO] Pyramids. Step: 1470000. Time Elapsed: 4398.072 s. Mean Reward: 1.720. Std of Reward: 0.380. Training.
132
+ [INFO] Pyramids. Step: 1500000. Time Elapsed: 4495.374 s. Mean Reward: 1.770. Std of Reward: 0.128. Training.
133
+ [INFO] Exported ./results/Pyramids Training/Pyramids/Pyramids-1499929.onnx
134
+ [INFO] Exported ./results/Pyramids Training/Pyramids/Pyramids-1500057.onnx
135
+ [INFO] Copied ./results/Pyramids Training/Pyramids/Pyramids-1500057.onnx to ./results/Pyramids Training/Pyramids.onnx.