elliemci commited on
Commit
9f60e47
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1 Parent(s): 7341b7f

more trained model

Browse files
README.md CHANGED
@@ -14,13 +14,19 @@ tags:
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  ## Usage (with ML-Agents)
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  The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
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  ### Resume the training
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  ```bash
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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 the Agent play
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- Watch Berrie the bear **hitting targets in browser**
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  1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
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  2. Step 1: Find your model_id: elliemci/ppo-Snowball-Target
 
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  ## Usage (with ML-Agents)
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  The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
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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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+ - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
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+ browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
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+ - A *longer tutorial* to understand how works ML-Agents:
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+ https://huggingface.co/learn/deep-rl-course/unit5/introduction
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+
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  ### Resume the training
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  ```bash
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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. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
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  2. Step 1: Find your model_id: elliemci/ppo-Snowball-Target
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config.json CHANGED
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- {"default_settings": null, "behaviors": {"SnowballTarget": {"trainer_type": "ppo", "hyperparameters": {"batch_size": 128, "buffer_size": 2048, "learning_rate": 0.0003, "beta": 0.005, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 3, "shared_critic": false, "learning_rate_schedule": "linear", "beta_schedule": "linear", "epsilon_schedule": "linear"}, "checkpoint_interval": 50000, "network_settings": {"normalize": false, "hidden_units": 256, "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": 10, "even_checkpoints": false, "max_steps": 200000, "time_horizon": 64, "summary_freq": 10000, "threaded": true, "self_play": null, "behavioral_cloning": null}}, "env_settings": {"env_path": "training-envs-executables/linux/SnowballTarget/SnowballTarget.x86_64", "env_args": null, "base_port": 5005, "num_envs": 1, "num_areas": 1, "timeout_wait": 60, "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, "no_graphics_monitor": false}, "environment_parameters": null, "checkpoint_settings": {"run_id": "SnowballTarget1", "initialize_from": null, "load_model": false, "resume": false, "force": false, "train_model": false, "inference": false, "results_dir": "results"}, "torch_settings": {"device": "cpu"}, "debug": false}
 
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configuration.yaml CHANGED
@@ -5,7 +5,7 @@ behaviors:
5
  hyperparameters:
6
  batch_size: 128
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  buffer_size: 2048
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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
@@ -14,7 +14,7 @@ behaviors:
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  learning_rate_schedule: linear
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  beta_schedule: linear
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  epsilon_schedule: linear
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- checkpoint_interval: 50000
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  network_settings:
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  normalize: false
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  hidden_units: 256
@@ -38,7 +38,7 @@ behaviors:
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  init_path: null
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  keep_checkpoints: 10
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@@ -59,7 +59,7 @@ engine_settings:
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  width: 84
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  height: 84
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@@ -69,11 +69,11 @@ checkpoint_settings:
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  run_id: SnowballTarget1
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  debug: false
 
5
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19
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  hidden_units: 256
 
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  no_graphics: true
 
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run_logs/Player-0.log CHANGED
@@ -2,9 +2,6 @@ Mono path[0] = '/content/drive/MyDrive/ColabNotebooks/DeepRL/unity_ml_agents/ml-
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  Mono config path = '/content/drive/MyDrive/ColabNotebooks/DeepRL/unity_ml_agents/ml-agents/training-envs-executables/linux/SnowballTarget/SnowballTarget_Data/MonoBleedingEdge/etc'
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- PlayerPrefs - Creating folder: /root/.config/unity3d/Hugging Face
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  Initialize engine version: 2021.3.14f1 (eee1884e7226)
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  [Subsystems] Discovering subsystems at path /content/drive/MyDrive/ColabNotebooks/DeepRL/unity_ml_agents/ml-agents/training-envs-executables/linux/SnowballTarget/SnowballTarget_Data/UnitySubsystems
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@@ -45,7 +42,7 @@ ERROR: Shader Standard shader is not supported on this GPU (none of subshaders/f
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@@ -53,7 +50,7 @@ Memory Statistics:
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