diff --git a/exp/kerokero/train.py b/exp/kerokero/train.py
--- a/exp/kerokero/train.py
+++ b/exp/kerokero/train.py
@@ -6,10 +6,9 @@ import logging as log
 import numpy as np
 from keras.layers import Conv2D,Dropout,Dense,Flatten,MaxPooling2D,BatchNormalization,GlobalAveragePooling2D
 from keras.models import Sequential,load_model
-from keras.callbacks import TensorBoard
+from keras.callbacks import TensorBoard,ModelCheckpoint
 
 import config as cfg
-import ftp
 
 parser=argparse.ArgumentParser()
 parser.add_argument("data")
@@ -78,12 +77,17 @@ with np.load(args.data) as data:
 	testLabels=data["testLabels"]
 log.info("done")
 
-tensorboard = TensorBoard(log_dir=os.path.join(cfg.thisDir,"../logs","{}".format(time())))
-BIG_STEP=20
-for i in range(args.initial_epoch//BIG_STEP,args.epochs//BIG_STEP):
-	model.fit(trainImages.reshape((-1,224,224,1)),trainLabels,epochs=(i+1)*BIG_STEP,initial_epoch=i*BIG_STEP,batch_size=20,validation_split=0.2,callbacks=[tensorboard])
-	path=args.save_model.format((i+1)*BIG_STEP)
-	log.info("saving model...")
-	model.save(path)
-	# ftp.push(path)
+tensorboard=TensorBoard(log_dir=os.path.join(args.log_dir,"{}".format(time())))
+checkpoint=ModelCheckpoint(args.save_model,monitor="val_loss",period=10)
+
+model.fit(
+	trainImages.reshape((-1,224,224,1)),
+	trainLabels,
+	epochs=args.epochs,
+	initial_epoch=args.initial_epoch,
+	batch_size=20,
+	validation_split=0.2,
+	callbacks=[tensorboard,checkpoint]
+)
+
 log.info(model.evaluate(testImages.reshape((-1,224,224,1)),testLabels))