updated settings file - easier mods during experiments

run.py

@@ -168,7 +168,7 @@ def train(data_parameters, training_parameters, network_parameters, misc_paramet
                                              'eps': training_parameters['optimizer_epsilon'],
                                              'weight_decay': training_parameters['optimizer_weigth_decay']
                                              },
-                        model_name=misc_parameters['model_name'],
+                        model_name=training_parameters['experiment_name'],
                         number_epochs=training_parameters['number_of_epochs'],
                         loss_log_period=training_parameters['loss_log_period'],
                         learning_rate_scheduler_step_size=training_parameters[

settings.ini

@@ -6,7 +6,7 @@ data_file = "/well/win-biobank/projects/imaging/data/data3/subjectsAll/subj_22k.
 k_fold = None
 data_split_flag = False
 test_percentage = 5
-subject_number = None
+subject_number = 600
 train_list = "datasets/train.txt"
 validation_list = "datasets/validation.txt"
 test_list = "datasets/test.txt"
@@ -20,26 +20,26 @@ mean_mask_path = "utils/mean_dr_stage2.nii.gz"
 mean_reduction = True
 
 [TRAINING]
-training_batch_size = 4
-validation_batch_size = 4
+experiment_name = "CU3D17-3"
+pre_trained_path = "saved_models/CU3D17-3.pth.tar"
+final_model_output_file = "CU3D17-3.pth.tar"
+training_batch_size = 3
+validation_batch_size = 3
 use_pre_trained = False
-pre_trained_path = "saved_models/finetuned_alldata.pth.tar"
-experiment_name = "experiment_name"
-learning_rate = 1e-4
+learning_rate = 1e-1
 optimizer_beta = (0.9, 0.999)
 optimizer_epsilon = 1e-8
 optimizer_weigth_decay = 1e-5
-number_of_epochs = 10
+number_of_epochs = 200
 loss_log_period = 50
-learning_rate_scheduler_step_size = 3
+learning_rate_scheduler_step_size = 5
 learning_rate_scheduler_gamma = 1e-1
 use_last_checkpoint = False
-final_model_output_file = "finetuned_alldata.pth.tar"
 
 [NETWORK]
-kernel_heigth = 5
-kernel_width = 5
-kernel_depth = 5
+kernel_heigth = 3
+kernel_width = 3
+kernel_depth = 3
 kernel_classification = 1
 input_channels = 1
 output_channels = 64
@@ -52,11 +52,10 @@ number_of_classes = 1
 
 [MISC]
 save_model_directory = "saved_models"
-model_name = "BrainMapper"
 logs_directory = "logs"
 checkpoint_directory = "checkpoints"
-device = 0
 experiments_directory = "experiments"
+device = 0
 
 [EVALUATION]
 trained_model_path = "saved_models/model.pth.tar"