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mieskolainen · Oct 20, 2024 · d89315a · d89315a
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Showing 10 changed files with 23 additions and 20 deletions.
diff --git a/configs/brem/models.yml b/configs/brem/models.yml
@@ -9,11 +9,12 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 
+
 # XGBoost
 # https://xgboost.readthedocs.io/en/latest/parameter.html
 xgb0:

diff --git a/configs/brem/models_reweight.yml b/configs/brem/models_reweight.yml
@@ -8,8 +8,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 

diff --git a/configs/brk/models.yml b/configs/brk/models.yml
@@ -8,10 +8,11 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
+
 ## Classifier setup
 
 # XGBoost

diff --git a/configs/dqcd/models.yml b/configs/dqcd/models.yml
@@ -12,8 +12,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 

diff --git a/configs/eid/models.yml b/configs/eid/models.yml
@@ -8,10 +8,11 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
+
 # - Keep the minibatch size small enough, otherwise weak convergence to optima with some models
 
 # Reference BDT (pre-computed in ROOT files)

diff --git a/configs/hgcal/models_cnd.yml b/configs/hgcal/models_cnd.yml
@@ -8,8 +8,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 

diff --git a/configs/hgcal/models_trk.yml b/configs/hgcal/models_trk.yml
@@ -8,8 +8,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 

diff --git a/configs/hnl/models.yml b/configs/hnl/models.yml
@@ -8,8 +8,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 4096
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 

diff --git a/configs/trg/models.yml b/configs/trg/models.yml
@@ -8,8 +8,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 1024
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  # 
 
 

diff --git a/configs/zee/models.yml b/configs/zee/models.yml
@@ -8,8 +8,8 @@ EVAL_PARAM: &EVAL_PARAM
   eval_batch_size: 4096
 
   # Post-training evaluation
-  readmode: -1                 # -1 finds the best loss model, -2 takes the last epoch model
-  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ...
+  readmode: -1                 # specific epoch (int), -1 finds the best loss model, -2 takes the last epoch model
+  readmode_metric: 'loss'      # e.g. 'loss', 'AUC' ... [currently only 'loss']
   readmode_operator: 'argmin'  #