eldraco commited on
Commit
cc37018
1 Parent(s): b17365e

Upload . with huggingface_hub

Browse files
.summary/0/events.out.tfevents.1677323897.groot ADDED
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README.md CHANGED
@@ -11,16 +11,16 @@ model-index:
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  type: reinforcement-learning
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  name: reinforcement-learning
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  dataset:
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- name: doom_health_gathering_supreme
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- type: doom_health_gathering_supreme
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  metrics:
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  - type: mean_reward
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- value: 14.27 +/- 5.47
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  name: mean_reward
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  verified: false
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  ---
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- A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
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  This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
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  Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
@@ -38,7 +38,7 @@ python -m sample_factory.huggingface.load_from_hub -r eldraco/rl_course_vizdoom_
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  To run the model after download, use the `enjoy` script corresponding to this environment:
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  ```
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- python -m <path.to.enjoy.module> --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme
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  ```
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@@ -49,7 +49,7 @@ See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
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  To continue training with this model, use the `train` script corresponding to this environment:
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  ```
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- python -m <path.to.train.module> --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme --restart_behavior=resume --train_for_env_steps=10000000000
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  ```
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  Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
 
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  type: reinforcement-learning
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  name: reinforcement-learning
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  dataset:
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+ name: doom_deathmatch_bots
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+ type: doom_deathmatch_bots
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  metrics:
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  - type: mean_reward
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+ value: 10.80 +/- 3.03
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  name: mean_reward
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  verified: false
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  ---
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+ A(n) **APPO** model trained on the **doom_deathmatch_bots** environment.
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  This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
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  Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
 
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  To run the model after download, use the `enjoy` script corresponding to this environment:
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  ```
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+ python -m <path.to.enjoy.module> --algo=APPO --env=doom_deathmatch_bots --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme
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  ```
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  To continue training with this model, use the `train` script corresponding to this environment:
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  ```
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+ python -m <path.to.train.module> --algo=APPO --env=doom_deathmatch_bots --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme --restart_behavior=resume --train_for_env_steps=10000000000
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  ```
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  Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
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config.json CHANGED
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  "wide_aspect_ratio": false,
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