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Hyperparam tunning - few epochs, high vf coeff (c1) - medium entropy coeff (c2) #64

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Hyperparam tunning - few epochs, high vf coeff (c1) - medium entropy coeff (c2) #64

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8 changes: 4 additions & 4 deletions main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,8 +46,8 @@ def train(config):
'mini_batch_size': 128,
'memory_size': 2000,
'eps': 0.2,
'c1': tune.quniform(0.5, 2.5, 0.25), # Value Function coeff
'c2': tune.quniform(0.00, 0.16, 0.02), # Entropy coeff
'c1': tune.quniform(1.5, 2.5, 0.5), # Value Function coeff
'c2': tune.quniform(0.00, 0.06, 0.02), # Entropy coeff
'lr': 1e-3, # Learning rate
'gamma': 0.99, # Discount rate
'log_interval': 10, # controls how often we log progress
Expand All @@ -56,14 +56,14 @@ def train(config):
'experiment': experiment,
'action_set_num': 4,
'train': True,
'seed': tune.grid_search([7081960, 1000, 190421])
'seed': 190421
}

analysis = tune.run(
train,
metric='running_reward',
mode='max',
num_samples=18,
num_samples=3,
resources_per_trial={"cpu": 0.4, "gpu": 0.3},
config=hyperparams,
)
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