Using AdamW, 1cycle policy. CV: 46%, LB: 32.4%

ngxbac · Jul 5, 2019 · 4b58ab1 · 4b58ab1
1 parent ac04128
commit 4b58ab1
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Showing 3 changed files with 13 additions and 11 deletions.
diff --git a/bin/train.sh b/bin/train.sh
@@ -4,7 +4,7 @@ export CUDA_VISIBLE_DEVICES=2,3
 RUN_CONFIG=config.yml
 
 
-LOGDIR=/raid/bac/kaggle/logs/recursion_cell/test/c123_s1/se_resnext50_32x4d/
+LOGDIR=/raid/bac/kaggle/logs/recursion_cell/test/c123_s1_1cycle_adamw/se_resnext50_32x4d/
 catalyst-dl run \
     --config=./configs/${RUN_CONFIG} \
     --logdir=$LOGDIR \

diff --git a/configs/config.yml b/configs/config.yml
@@ -22,14 +22,16 @@ stages:
     criterion: CrossEntropyLoss
 
   optimizer_params:
-    optimizer: Adam
-    lr: 0.0003
-    weight_decay: 0.0001
+    optimizer: AdamW
+    lr: 0.0001
+#    weight_decay: 0.0001
 
   scheduler_params:
-    scheduler: MultiStepLR
-    milestones: [25, 30, 40]
-    gamma: 0.5
+    scheduler: OneCycleLR
+    num_steps: &num_epochs 30
+    lr_range: [0.0005, 0.00001]
+    warmup_steps: 5
+    momentum_range: [0.85, 0.95]
 
   data_params:
     batch_size: 64
@@ -46,7 +48,7 @@ stages:
   stage1:
 
     state_params:
-      num_epochs: 45
+      num_epochs: *num_epochs
 
     callbacks_params: &callback_params
       loss:

diff --git a/src/make_submission.py b/src/make_submission.py
@@ -35,7 +35,7 @@ def predict(model, loader):
 def predict_all():
     test_csv = '/raid/data/kaggle/recursion-cellular-image-classification/test.csv'
     # test_csv = './csv/valid_0.csv'
-    log_dir = "/raid/bac/kaggle/logs/recursion_cell/test/c123_s1_concatpool/se_resnext50_32x4d/"
+    log_dir = "/raid/bac/kaggle/logs/recursion_cell/test/c123_s1_1cycle_adamw/se_resnext50_32x4d/"
     root = "/raid/data/kaggle/recursion-cellular-image-classification/"
     site = 1
     channels = [1,2,3]
@@ -75,8 +75,8 @@ def predict_all():
     submission = df.copy()
     submission['sirna'] = all_preds.astype(int)
     os.makedirs("submission", exist_ok=True)
-    submission.to_csv('./submission/se_resnext50_32x4d_c123_s1_concatpool.csv', index=False, columns=['id_code', 'sirna'])
-    np.save("./submission/se_resnext50_32x4d_c123_s1_concatpool.npy", pred)
+    submission.to_csv('./submission/se_resnext50_32x4d_c123_s1_1cycle_adamw.csv', index=False, columns=['id_code', 'sirna'])
+    np.save("./submission/se_resnext50_32x4d_c123_s1_1cycle_adamw.npy", pred)
 
 
 if __name__ == '__main__':