Guide: First Push
Browse files- README.md +31 -0
- SoccerTwos/SoccerTwos-1499912.onnx +3 -0
- SoccerTwos/SoccerTwos-1499912.pt +3 -0
- SoccerTwos/SoccerTwos-1999722.onnx +3 -0
- SoccerTwos/SoccerTwos-1999722.pt +3 -0
- SoccerTwos/SoccerTwos-2499793.onnx +3 -0
- SoccerTwos/SoccerTwos-2499793.pt +3 -0
- SoccerTwos/SoccerTwos-2999820.onnx +3 -0
- SoccerTwos/SoccerTwos-2999820.pt +3 -0
- SoccerTwos/SoccerTwos-3499876.onnx +3 -0
- SoccerTwos/SoccerTwos-3499876.pt +3 -0
- SoccerTwos/SoccerTwos-3499993.onnx +3 -0
- SoccerTwos/SoccerTwos-3499993.pt +3 -0
- SoccerTwos/SoccerTwos-3999955.onnx +3 -0
- SoccerTwos/SoccerTwos-3999955.pt +3 -0
- SoccerTwos/SoccerTwos-4499976.onnx +3 -0
- SoccerTwos/SoccerTwos-4499976.pt +3 -0
- SoccerTwos/SoccerTwos-4499998.onnx +3 -0
- SoccerTwos/SoccerTwos-4499998.pt +3 -0
- SoccerTwos/SoccerTwos-499466.pt +3 -0
- SoccerTwos/SoccerTwos-4999980.onnx +3 -0
- SoccerTwos/SoccerTwos-4999980.pt +3 -0
- SoccerTwos/SoccerTwos-5499994.onnx +3 -0
- SoccerTwos/SoccerTwos-5499994.pt +3 -0
- SoccerTwos/SoccerTwos-5999990.onnx +3 -0
- SoccerTwos/SoccerTwos-5999990.pt +3 -0
- SoccerTwos/checkpoint.pt +3 -0
- SoccerTwos/events.out.tfevents.1685366793.DESKTOP-N831AT2.20188.0 +3 -0
- SoccerTwos/events.out.tfevents.1685368489.DESKTOP-N831AT2.2508.0 +3 -0
- SoccerTwos/events.out.tfevents.1685462139.DESKTOP-N831AT2.692.0 +3 -0
- SoccerTwos/events.out.tfevents.1685516271.DESKTOP-N831AT2.18264.0 +3 -0
- config.json +1 -0
- configuration.yaml +82 -0
- run_logs/Player-0.log +42 -0
- run_logs/timers.json +363 -0
- run_logs/training_status.json +10 -0
README.md
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---
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tags:
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- unity-ml-agents
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- ml-agents
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- deep-reinforcement-learning
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- reinforcement-learning
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- ML-Agents-SoccerTwos
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library_name: ml-agents
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---
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# **poca** Agent playing **SoccerTwos**
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This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
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## Usage (with ML-Agents)
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The Documentation: https://github.com/huggingface/ml-agents#get-started
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We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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### Resume the training
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```
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mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
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```
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### Watch your Agent play
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You can watch your agent **playing directly in your browser:**.
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1. Go to https://huggingface.co/spaces/unity/ML-Agents-SoccerTwos
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2. Step 1: Write your model_id: hruslen/poca-SoccerTwos
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3. Step 2: Select your *.nn /*.onnx file
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4. Click on Watch the agent play 👀
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config.json
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{"default_settings": null, "behaviors": {"SoccerTwos": {"trainer_type": "poca", "hyperparameters": {"batch_size": 2048, "buffer_size": 20480, "learning_rate": 0.0003, "beta": 0.005, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 3, "learning_rate_schedule": "constant", "beta_schedule": "constant", "epsilon_schedule": "constant"}, "checkpoint_interval": 500000, "network_settings": {"normalize": false, "hidden_units": 512, "num_layers": 2, "vis_encode_type": "simple", "memory": null, "goal_conditioning_type": "hyper", "deterministic": false}, "reward_signals": {"extrinsic": {"gamma": 0.99, "strength": 1.0, "network_settings": {"normalize": false, "hidden_units": 128, "num_layers": 2, "vis_encode_type": "simple", "memory": null, "goal_conditioning_type": "hyper", "deterministic": false}}}, "init_path": null, "keep_checkpoints": 5, "even_checkpoints": false, "max_steps": 50000000, "time_horizon": 1000, "summary_freq": 10000, "threaded": false, "self_play": {"save_steps": 50000, "team_change": 200000, "swap_steps": 2000, "window": 10, "play_against_latest_model_ratio": 0.5, "initial_elo": 1200.0}, "behavioral_cloning": null}}, "env_settings": {"env_path": "./training-envs-executables/SoccerTwos.exe", "env_args": null, "base_port": 5005, "num_envs": 1, "num_areas": 1, "seed": -1, "max_lifetime_restarts": 10, "restarts_rate_limit_n": 1, "restarts_rate_limit_period_s": 60}, "engine_settings": {"width": 84, "height": 84, "quality_level": 5, "time_scale": 20, "target_frame_rate": -1, "capture_frame_rate": 60, "no_graphics": true}, "environment_parameters": null, "checkpoint_settings": {"run_id": "SoccerTwos", "initialize_from": null, "load_model": false, "resume": false, "force": false, "train_model": false, "inference": false, "results_dir": "results"}, "torch_settings": {"device": null}, "debug": false}
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configuration.yaml
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default_settings: null
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behaviors:
|
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SoccerTwos:
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trainer_type: poca
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hyperparameters:
|
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batch_size: 2048
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buffer_size: 20480
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learning_rate: 0.0003
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beta: 0.005
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epsilon: 0.2
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lambd: 0.95
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num_epoch: 3
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learning_rate_schedule: constant
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beta_schedule: constant
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epsilon_schedule: constant
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checkpoint_interval: 500000
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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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memory: null
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goal_conditioning_type: hyper
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deterministic: false
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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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network_settings:
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normalize: false
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hidden_units: 128
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num_layers: 2
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33 |
+
vis_encode_type: simple
|
34 |
+
memory: null
|
35 |
+
goal_conditioning_type: hyper
|
36 |
+
deterministic: false
|
37 |
+
init_path: null
|
38 |
+
keep_checkpoints: 5
|
39 |
+
even_checkpoints: false
|
40 |
+
max_steps: 50000000
|
41 |
+
time_horizon: 1000
|
42 |
+
summary_freq: 10000
|
43 |
+
threaded: false
|
44 |
+
self_play:
|
45 |
+
save_steps: 50000
|
46 |
+
team_change: 200000
|
47 |
+
swap_steps: 2000
|
48 |
+
window: 10
|
49 |
+
play_against_latest_model_ratio: 0.5
|
50 |
+
initial_elo: 1200.0
|
51 |
+
behavioral_cloning: null
|
52 |
+
env_settings:
|
53 |
+
env_path: ./training-envs-executables/SoccerTwos.exe
|
54 |
+
env_args: null
|
55 |
+
base_port: 5005
|
56 |
+
num_envs: 1
|
57 |
+
num_areas: 1
|
58 |
+
seed: -1
|
59 |
+
max_lifetime_restarts: 10
|
60 |
+
restarts_rate_limit_n: 1
|
61 |
+
restarts_rate_limit_period_s: 60
|
62 |
+
engine_settings:
|
63 |
+
width: 84
|
64 |
+
height: 84
|
65 |
+
quality_level: 5
|
66 |
+
time_scale: 20
|
67 |
+
target_frame_rate: -1
|
68 |
+
capture_frame_rate: 60
|
69 |
+
no_graphics: true
|
70 |
+
environment_parameters: null
|
71 |
+
checkpoint_settings:
|
72 |
+
run_id: SoccerTwos
|
73 |
+
initialize_from: null
|
74 |
+
load_model: false
|
75 |
+
resume: false
|
76 |
+
force: false
|
77 |
+
train_model: false
|
78 |
+
inference: false
|
79 |
+
results_dir: results
|
80 |
+
torch_settings:
|
81 |
+
device: null
|
82 |
+
debug: false
|
run_logs/Player-0.log
ADDED
@@ -0,0 +1,42 @@
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|
1 |
+
Mono path[0] = 'D:/OneDrive/Documents/rlhf/ml-agents/training-envs-executables/SoccerTwos/SoccerTwos_Data/Managed'
|
2 |
+
Mono config path = 'D:/OneDrive/Documents/rlhf/ml-agents/training-envs-executables/SoccerTwos/MonoBleedingEdge/etc'
|
3 |
+
Initialize engine version: 2021.3.14f1 (eee1884e7226)
|
4 |
+
[Subsystems] Discovering subsystems at path D:/OneDrive/Documents/rlhf/ml-agents/training-envs-executables/SoccerTwos/SoccerTwos_Data/UnitySubsystems
|
5 |
+
Forcing GfxDevice: Null
|
6 |
+
GfxDevice: creating device client; threaded=0; jobified=0
|
7 |
+
NullGfxDevice:
|
8 |
+
Version: NULL 1.0 [1.0]
|
9 |
+
Renderer: Null Device
|
10 |
+
Vendor: Unity Technologies
|
11 |
+
Begin MonoManager ReloadAssembly
|
12 |
+
- Completed reload, in 11.613 seconds
|
13 |
+
ERROR: Shader Sprites/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
14 |
+
Microsoft Media Foundation video decoding to texture disabled: graphics device is Null, only Direct3D 11 and Direct3D 12 (only on desktop) are supported for hardware-accelerated video decoding.
|
15 |
+
ERROR: Shader Sprites/Mask shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
16 |
+
ERROR: Shader Legacy Shaders/VertexLit shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
17 |
+
WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed
|
18 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
19 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
20 |
+
ERROR: Shader Standard (Specular setup) shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
21 |
+
WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed
|
22 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
23 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
24 |
+
WARNING: Shader Unsupported: 'Autodesk Interactive' - All subshaders removed
|
25 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
26 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
27 |
+
ERROR: Shader Autodesk Interactive shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
28 |
+
WARNING: Shader Unsupported: 'Autodesk Interactive' - All subshaders removed
|
29 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
30 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
31 |
+
WARNING: Shader Unsupported: 'Standard' - All subshaders removed
|
32 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
33 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
34 |
+
ERROR: Shader Standard shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
35 |
+
WARNING: Shader Unsupported: 'Standard' - All subshaders removed
|
36 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
37 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
38 |
+
UnloadTime: 0.653900 ms
|
39 |
+
Registered Communicator in Agent.
|
40 |
+
ERROR: Shader UI/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
41 |
+
GRPC Exception: Status(StatusCode=Unknown, Detail="Stream removed"). Disconnecting from trainer.
|
42 |
+
Setting up 4 worker threads for Enlighten.
|
run_logs/timers.json
ADDED
@@ -0,0 +1,363 @@
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
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|
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|
|
|
|
|
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|
|
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|
|
|
|
|
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|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"name": "root",
|
3 |
+
"gauges": {
|
4 |
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"SoccerTwos.Policy.Entropy.mean": {
|
5 |
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"value": 3.208897352218628,
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6 |
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"min": 3.167426347732544,
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"max": 3.295755386352539,
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8 |
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"count": 50
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9 |
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},
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10 |
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"SoccerTwos.Policy.Entropy.sum": {
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11 |
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"value": 72084.671875,
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12 |
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"min": 3157.7578125,
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13 |
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"max": 105464.1640625,
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14 |
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"count": 50
|
15 |
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},
|
16 |
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"SoccerTwos.Environment.EpisodeLength.mean": {
|
17 |
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"value": 723.8333333333334,
|
18 |
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"min": 400.5833333333333,
|
19 |
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"max": 999.0,
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20 |
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"count": 50
|
21 |
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},
|
22 |
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"SoccerTwos.Environment.EpisodeLength.sum": {
|
23 |
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"value": 17372.0,
|
24 |
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"min": 12368.0,
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25 |
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"max": 28232.0,
|
26 |
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"count": 50
|
27 |
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},
|
28 |
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"SoccerTwos.Self-play.ELO.mean": {
|
29 |
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"value": 1215.3275069722,
|
30 |
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"min": 1198.0140976835446,
|
31 |
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"max": 1216.0444001507303,
|
32 |
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"count": 46
|
33 |
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},
|
34 |
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"SoccerTwos.Self-play.ELO.sum": {
|
35 |
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"value": 9722.6200557776,
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36 |
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"min": 2396.5239063568742,
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37 |
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"max": 19400.876835675528,
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38 |
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"count": 46
|
39 |
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},
|
40 |
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"SoccerTwos.Step.mean": {
|
41 |
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"value": 499466.0,
|
42 |
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"min": 9138.0,
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43 |
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"max": 499466.0,
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44 |
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"count": 50
|
45 |
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},
|
46 |
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"SoccerTwos.Step.sum": {
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47 |
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"value": 499466.0,
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48 |
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"min": 9138.0,
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49 |
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"max": 499466.0,
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50 |
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"count": 50
|
51 |
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},
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52 |
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"SoccerTwos.Policy.ExtrinsicBaselineEstimate.mean": {
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"value": -0.0007608662126585841,
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},
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"value": -0.009891260415315628,
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"count": 50
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"value": 0.0,
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"min": 0.0,
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"max": 0.0,
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"count": 50
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},
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"SoccerTwos.Environment.CumulativeReward.sum": {
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"value": 0.0,
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"min": 0.0,
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|
117 |
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},
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"SoccerTwos.IsTraining.sum": {
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"value": 1.0,
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},
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"min": 0.013953804352786392,
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"max": 0.02250218946040453,
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"count": 23
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},
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"value": 0.0015458971553016453,
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"min": 0.0005459430918563158,
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"count": 23
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159 |
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"SoccerTwos.Policy.LearningRate.mean": {
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"value": 0.0003,
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162 |
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"min": 0.0003,
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"max": 0.0003,
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run_logs/training_status.json
ADDED
@@ -0,0 +1,10 @@
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{
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