Modification for trainings and log file name

egs/iemocap/config/custom/Iemocap.yaml

@@ -9,7 +9,7 @@ dataset_csv: list/iemocap_ses3-test.csv
 sample_rate: 16000
 
 validation_ratio: 0.02
-batch_size: 4
+batch_size: 100
 
 # Training set
 train:
@@ -18,7 +18,7 @@ train:
   overlap: 3.
 
   sampler:
-    examples_per_speaker: 1
+    examples_per_speaker: 25
     samples_per_speaker: 100
     augmentation_replica: 1
 

egs/iemocap/config/custom/modification_yaml.py

@@ -21,7 +21,7 @@ session_test = args.session_test
 lr = args.lr
 tmp = "model_custom/tmp_custom_{}emo_{}batch_lr-{}_Test-IEMOCAP{}.pt".format(nb_cate, batch, lr, session_test)
 best = "model_custom/best_custom_{}emo_{}batch_lr-{}_Test-IEMOCAP{}.pt".format(nb_cate, batch, lr, session_test)
-log = "logs/half_resnet34_{}emo_{}batch_lr-{}_Test-IEMOCAP{}.log".format(nb_cate, batch, lr, session_test)
+log = "logs/custom_{}emo_{}batch_lr-{}_Test-IEMOCAP{}.log".format(nb_cate, batch, lr, session_test)
 
 ## Modification of variables in YAML files
 # model.yaml

egs/iemocap/config/custom/training.yaml

 # Training description
 
 # General options
-log_file: logs/half_resnet34_4emo_4batch_lr-0.0001_Test-IEMOCAP3.log
+log_file: logs/half_resnet34_4emo_100batch_lr-0.0001_Test-IEMOCAP3.log
 torch_seed: 42
 numpy_seed: 42
 random_seed: 42
@@ -35,6 +35,6 @@ log_interval: 50
 validation_frequency: 1
 
 # Save options
-tmp_model_name: model_custom/tmp_custom_4emo_4batch_lr-0.0001_Test-IEMOCAP3.pt
-best_model_name: model_custom/best_custom_4emo_4batch_lr-0.0001_Test-IEMOCAP3.pt
+tmp_model_name: model_custom/tmp_custom_4emo_100batch_lr-0.0001_Test-IEMOCAP3.pt
+best_model_name: model_custom/best_custom_4emo_100batch_lr-0.0001_Test-IEMOCAP3.pt
 checkpoint_frequency: