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rl_course_vizdoom_health_gathering_supreme

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rl_course_vizdoom_health_gathering_supreme
File size: 4,643 Bytes 
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{
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  "env": "doom_health_gathering_supreme",
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  "restart_behavior": "resume",
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  "batched_sampling": false,
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  "worker_num_splits": 2,
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  "max_policy_lag": 1000,
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  "shuffle_minibatches": false,
  "gamma": 0.99,
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  "exploration_loss_coeff": 0.001,
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  "exploration_loss": "symmetric_kl",
  "gae_lambda": 0.95,
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  "optimizer": "adam",
  "adam_eps": 1e-06,
  "adam_beta1": 0.9,
  "adam_beta2": 0.999,
  "max_grad_norm": 0.0,
  "learning_rate": 0.0001,
  "lr_schedule": "constant",
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  "obs_subtract_mean": 0.0,
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  "load_checkpoint_kind": "latest",
  "save_milestones_sec": -1,
  "save_best_every_sec": 5,
  "save_best_metric": "reward",
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  "benchmark": false,
  "encoder_mlp_layers": [
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  "encoder_conv_architecture": "convnet_simple",
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  "rnn_size": 512,
  "rnn_type": "lstm",
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  "decoder_mlp_layers": [],
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  "wandb_project": "sample_factory",
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  "num_humans": 0,
  "num_bots": -1,
  "start_bot_difficulty": null,
  "timelimit": null,
  "res_w": 128,
  "res_h": 72,
  "wide_aspect_ratio": false,
  "eval_env_frameskip": 1,
  "fps": 35,
  "command_line": "--train_for_seconds=3600000 --algo=APPO --gamma=0.99 --use_rnn=True --num_workers=8 --num_envs_per_worker=12 --num_epochs=1 --rollout=32 --recurrence=32 --batch_size=2048 --benchmark=False --max_grad_norm=0.0 --decorrelate_experience_max_seconds=1 --nonlinearity=relu --rnn_type=lstm --num_policies=1 --heartbeat_reporting_interval=300 --train_dir=/home/knight/github/huggingface-deep-rl-course/unit8/train_dir --seed=2222 --experiment=default_experiment --env=doom_health_gathering_supreme",
  "cli_args": {
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    "env": "doom_health_gathering_supreme",
    "experiment": "default_experiment",
    "train_dir": "/home/knight/github/huggingface-deep-rl-course/unit8/train_dir",
    "seed": 2222,
    "num_policies": 1,
    "num_workers": 8,
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    "batch_size": 2048,
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    "heartbeat_reporting_interval": 300,
    "train_for_seconds": 3600000,
    "benchmark": false,
    "use_rnn": true,
    "rnn_type": "lstm",
    "nonlinearity": "relu"
  }
}