chore: bunch of small stuff

Former-commit-id: e6eea69309c723face4c1f09ad935451ce715eee [formerly f59c07f943f0cddc6db2a0512923f2960a2400bd]
Former-commit-id: 0e2f44ec2b051ca2b31fe16c59e6702a6890701c

src/train.py

@@ -47,7 +47,6 @@ if __name__ == "__main__":
     )
 
     # load checkpoint
-    # module.load_state_dict(torch.load()["state_dict"])
     # module.load_from_checkpoint("/tmp/model.ckpt")
 
     # log gradients and weights regularly
@@ -68,10 +67,10 @@ if __name__ == "__main__":
         precision=wandb.config.PRECISION,
         logger=logger,
         log_every_n_steps=5,
-        val_check_interval=50,
+        val_check_interval=200,
         callbacks=[
-            EarlyStopping(monitor="valid/map", mode="max", patience=10, min_delta=0.01),
-            ModelCheckpoint(monitor="valid/map", mode="max"),
+            EarlyStopping(monitor="valid/bbox/map", mode="max", patience=10, min_delta=0.01),
+            ModelCheckpoint(monitor="valid/bbox/map", mode="max"),
             # ModelPruning("l1_unstructured", amount=0.5),
             LearningRateMonitor(log_momentum=True),
             RichModelSummary(max_depth=2),

src/utils/paste.py

@@ -24,7 +24,7 @@ class RandomPaste(A.DualTransform):
         self,
         nb,
         image_dir,
-        scale_range=(0.05, 0.5),
+        scale_range=(0.02, 0.3),
         always_apply=True,
         p=1.0,
     ):

wandb.yaml

@@ -28,17 +28,17 @@ WORKERS:
   value: 16
 
 EPOCHS:
-  value: 100
+  value: 50
 TRAIN_BATCH_SIZE:
-  value: 10
+  value: 6
 VALID_BATCH_SIZE:
   value: 2
 PREFETCH_FACTOR:
   value: 2
 
 LEARNING_RATE:
-  value: 0.0005
+  value: 0.001
 WEIGHT_DECAY:
-  value: 0.0005
+  value: 0.0001
 MOMENTUM:
   value: 0.9