Update fine_tuning_config.yaml

config/fine_tuning_config.yaml

@@ -2,20 +2,27 @@ trainer: "BasicTrainer"
 random_seed: 43
 
 model:
-  type: "efficientnet_b1"
+  type: "efficientnet_b0"
   parameters:
-    num_classes: 394
+    num_classes: 34
     pretrained: true
 
 training:
   batch_size: 32
   epochs:
-    initial: 1
-    fine_tuning: 1
+    initial: 100
+    fine_tuning: 10
+  loss_function:
+    type: "CrossEntropyLoss"
+    parameters: {}
+  optimizer:
+    type: "Adam"
+    parameters:
+      learning_rate: 0.005
   learning_rates:
-    initial: 0.001
-    fine_tuning: 0.0001
-    final_fine_tuning: 0.00001
+    initial: 0.01
+    fine_tuning: 0.001
+    final_fine_tuning: 0.0001
   freeze_until_layer: "classifier.1.weight"
 
 metrics:
@@ -24,20 +31,50 @@ metrics:
   - type: "Recall"
   - type: "F1Score"
 
+callbacks:
+  CSVLogging:
+    parameters:
+      csv_path: "dinamically/set/by/date.csv"
+  Checkpoint:
+    parameters:
+      save_freq: 1
+  EarlyStopping:
+    parameters:
+      monitor: "val_loss"
+      patience: 10
+      delta: 0.01
+      verbose: true
+
 data:
   name: "CarDataset"
-  dataset_path: "./data/processed/BD-461"
+  dataset_path: "./data/processed/DB_Marca"
   test_size: 0.2
   val_size: 0.1
   transforms:
     - type: "Resize"
       parameters:
         size: [240, 240]
+    - type: "AutoAugment"
+      parameters: {}
     - type: "ToTensor"
       parameters: {}
     - type: "Normalize"
+      parameters:
+        mean: [0.485, 0.456, 0.406]
+        std: [0.229, 0.224, 0.225]
+  eval_transforms:
+    - type: "Resize"
+      parameters:
+        size: [240, 240]
+    - type: "ToTensor"
       parameters: {}
+    - type: "Normalize"
+      parameters:
+        mean: [0.485, 0.456, 0.406]
+        std: [0.229, 0.224, 0.225]
 
 paths:
+  model_path: "./outputs/models/"
   log_path: "./logs/"
   plot_path: "./outputs/figures/"
+  checkpoint_path: "./outputs/checkpoints/"