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schedule_nuswide_full_accv_mod.py
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schedule_nuswide_full_accv_mod.py
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from train import Train
if __name__ == '__main__':
path = "exp_nuswide_full_accv_mod"
train = Train()
experiments = [
# NUS_WIDE 2100._
{
"dataset": "nus2100._",
"loss": "loss_accv_mod",
"hash_size": 24,
"margin": 0.5,
"batch_size": 150,
"total_epoch_count": 28,
"number_of_epochs_per_decay": 30,
"weight_decay_factor": 5e-05,
"learning_rate": 0.07,
"learning_rate_decay_factor": 2.0 / 3.0
},
{
"dataset": "nus2100._",
"loss": "loss_accv_mod",
"hash_size": 16,
"margin": 2.0,
"batch_size": 150,
"total_epoch_count": 28,
"number_of_epochs_per_decay": 30,
"weight_decay_factor": 5e-05,
"learning_rate": 0.07,
"learning_rate_decay_factor": 2.0 / 3.0
},
{
"dataset": "nus2100._",
"loss": "loss_accv_mod",
"hash_size": 32,
"margin": 0.5,
"batch_size": 150,
"total_epoch_count": 28,
"number_of_epochs_per_decay": 30,
"weight_decay_factor": 5e-05,
"learning_rate": 0.07,
"learning_rate_decay_factor": 2.0 / 3.0
},
{
"dataset": "nus2100._",
"loss": "loss_accv_mod",
"hash_size": 48,
"margin": 0.5,
"batch_size": 150,
"total_epoch_count": 28,
"number_of_epochs_per_decay": 30,
"weight_decay_factor": 5e-05,
"learning_rate": 0.07,
"learning_rate_decay_factor": 2.0 / 3.0
},
]
for e in experiments:
train.run(path, e)