I am currently implementing SubspaceNet for the broadband coherent scenario, and I am attempting to reproduce the performance reported in Table III of the paper. However, I am facing difficulties in reproducing the reported loss/performance values and would appreciate clarification regarding the training configuration used.
I generated datasets:
Generic_DataSet_Broadband_coherent_45000_M=2_N=8_T=200_SNR=10_eta=0_sv_noise_var0_bias=0 and SubspaceNet_DataSet_Broadband_coherent_45000_M=2_N=8_T=200_SNR=10_eta=0_sv_noise_var0_bias=0.
However, I observe relatively high loss (~0.56 (rad) at epoch 30), which does not seem to align with the performance trends in Table III. Hyperparameters used are as follows:
simulation_parameters = (
TrainingParams()
.set_batch_size(2048)
.set_epochs(80)
# .set_model(system_model=samples_model, tau=model.tau, diff_method=model.diff_method)
.set_model(model=model_config)
.set_optimizer(optimizer="Adam", learning_rate=0.001, weight_decay=1e-9)
.set_training_dataset(train_dataset)
.set_schedular(step_size=80, gamma=0.2)
.set_criterion()
)
I would like to confirm whether: My dataset size may be insufficient, or Broadband configuration requires different hyperparameters.
Any clarification regarding the exact training setup used for the broadband coherent scenario would be greatly appreciated.
Thank you in advance for your support and guidance.
I am currently implementing SubspaceNet for the broadband coherent scenario, and I am attempting to reproduce the performance reported in Table III of the paper. However, I am facing difficulties in reproducing the reported loss/performance values and would appreciate clarification regarding the training configuration used.
I generated datasets:
Generic_DataSet_Broadband_coherent_45000_M=2_N=8_T=200_SNR=10_eta=0_sv_noise_var0_bias=0 and SubspaceNet_DataSet_Broadband_coherent_45000_M=2_N=8_T=200_SNR=10_eta=0_sv_noise_var0_bias=0.
However, I observe relatively high loss (~0.56 (rad) at epoch 30), which does not seem to align with the performance trends in Table III. Hyperparameters used are as follows:
simulation_parameters = (
TrainingParams()
.set_batch_size(2048)
.set_epochs(80)
# .set_model(system_model=samples_model, tau=model.tau, diff_method=model.diff_method)
.set_model(model=model_config)
.set_optimizer(optimizer="Adam", learning_rate=0.001, weight_decay=1e-9)
.set_training_dataset(train_dataset)
.set_schedular(step_size=80, gamma=0.2)
.set_criterion()
)
I would like to confirm whether: My dataset size may be insufficient, or Broadband configuration requires different hyperparameters.
Any clarification regarding the exact training setup used for the broadband coherent scenario would be greatly appreciated.
Thank you in advance for your support and guidance.