--- a
+++ b/configs/config_toan.yml
@@ -0,0 +1,105 @@
+model_params:
+  model: &model CNNFinetuneModels
+  model_name: &model_name densenet169
+  num_classes: 6
+
+
+args:
+  expdir: "src"
+  logdir: &logdir "./logs/rsna"
+  baselogdir: "./logs/rsna"
+
+distributed_params:
+  opt_level: O1
+
+stages:
+
+  state_params:
+    main_metric: &reduce_metric loss
+    minimize_metric: True
+
+  criterion_params:
+    criterion: &criterion LogLoss
+    weight: [1,1,1,1,1,2]
+
+  data_params:
+    batch_size: 32
+    num_workers: 4
+    drop_last: False
+
+    image_size: &image_size [512, 512]
+    train_csv: "./csv/stratified_kfold/train_0.csv.gz"
+    valid_csv: "./csv/stratified_kfold/valid_0.csv.gz"
+#    dataset_type: "RSNAMultiWindowsDataset"
+    with_any: True
+    root: "../stage_1_train_images_jpg_preprocessing/"
+    image_type: "jpg"
+
+  warmup:
+    optimizer_params:
+      optimizer: AdamW
+      lr: 0.001
+
+    scheduler_params:
+      scheduler: MultiStepLR
+      milestones: [10]
+      gamma: 0.3
+
+    state_params:
+      num_epochs: 3
+
+    callbacks_params: &callbacks_params
+      loss:
+        callback: CriterionCallback
+
+      optimizer:
+        callback: OptimizerCallback
+        accumulation_steps: 1
+      scheduler:
+        callback: SchedulerCallback
+        reduce_metric: *reduce_metric
+      saver:
+        callback: CheckpointCallback
+        save_n_best: 5
+
+  stage1:
+
+    optimizer_params:
+      optimizer: AdamW
+      lr: 0.0001
+
+    scheduler_params:
+      scheduler: ReduceLROnPlateau
+      patience: 1
+      min_lr: 0.00001
+      verbose: True
+#      scheduler: OneCycleLR
+#      num_steps: &num_epochs 25
+#      lr_range: [0.0005, 0.00001]
+#      warmup_steps: 5
+#      momentum_range: [0.85, 0.95]
+
+    state_params:
+      num_epochs: 20
+
+    callbacks_params:
+      loss:
+        callback: CriterionCallback
+
+      optimizer:
+        callback: OptimizerCallback
+        accumulation_steps: 1
+      scheduler:
+        callback: SchedulerCallback
+        reduce_metric: *reduce_metric
+      saver:
+        callback: CheckpointCallback
+        save_n_best: 5
+
+      early_stoping:
+        callback: EarlyStoppingCallback
+        patience: 2
+
+monitoring_params:
+  project: "Kaggle-RSNA"
+  tags: [*model, *model_name, *criterion]
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