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folders:
parent_dir: "./results/"
model_name: "sr6_128x4_das_nc"
settings:
game_id: "umk3"
step_ratio: 6
frame_shape: !!python/tuple [128, 128, 1]
continue_game: 0.0
action_space: "discrete"
characters: "Skorpion"
difficulty: 5
wrappers_settings:
normalize_reward: true
no_attack_buttons_combinations: true
stack_frames: 4
dilation: 1
add_last_action: true
stack_actions: 12
scale: true
exclude_image_scaling: true
role_relative: true
flatten: true
filter_keys: ["action", "own_health", "opp_health", "own_side", "opp_side", "opp_character", "stage", "timer"]
# optuna results
# Best hyperparameters: {'gamma': 0.05944028113410932, 'max_grad_norm': 3.5407661656818026,
# 'exponent_n_steps': 5, 'n_epochs': 14, 'batch_size': 512, 'lr': 0.014638860976621421,
# 'ent_coef': 2.361611947920214e-06, 'clip_range': 0.3, 'gae_lambda': 0.9520674913500098,
# 'vf_coef': 0.6420316461542878, 'net_arch': 'medium', 'activation_fn': 'leaky_relu'}
policy_kwargs:
#net_arch: [{ pi: [64, 64], vf: [32, 32] }]
net_arch: [256, 256]
activation_fn: "leaky_relu"
ppo_settings:
gamma: 0.94
model_checkpoint: "660000" # 0: No checkpoint, else: Load checkpoint (if previously trained)
learning_rate: [1.0e-3, 2.5e-6] # To start
clip_range: [0.3, 0.015] # To start
batch_size: 512 #8 #nminibatches gave different batch size depending on the number of environments: batch_size = (n_steps * n_envs) // nminibatches
n_epochs: 14
n_steps: 512
gae_lambda: 0.9520674913500098
ent_coef: 2.361611947920214e-06
vf_coef: 0.6420316461542878
autosave_freq: 50000
time_steps: 1000000
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