diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..ed13d84
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,29 @@
+BSD 3-Clause License
+
+Copyright (c) 2020, princeton-vl
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+* Neither the name of the copyright holder nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/train.py b/train.py
index f5a99e1..2767acf 100755
--- a/train.py
+++ b/train.py
@@ -21,7 +21,7 @@ import datasets
 
 # exclude extremly large displacements
 MAX_FLOW = 1000
-SUM_FREQ = 1000
+SUM_FREQ = 100
 VAL_FREQ = 5000
 
 
@@ -86,7 +86,7 @@ def fetch_optimizer(args, model):
     optimizer = optim.AdamW(model.parameters(), lr=args.lr, weight_decay=args.wdecay, eps=args.epsilon)
 
     scheduler = optim.lr_scheduler.OneCycleLR(optimizer, args.lr, args.num_steps,
-        pct_start=0.2, cycle_momentum=False, anneal_strategy='linear', final_div_factor=0.05)
+        pct_start=0.2, cycle_momentum=False, anneal_strategy='linear', final_div_factor=1.0)
 
     return optimizer, scheduler
     
@@ -208,4 +208,4 @@ if __name__ == '__main__':
     args.batch_size = args.batch_size * num_gpus
     args.lr = args.lr * num_gpus
 
-    train(args)
\ No newline at end of file
+    train(args)