diff --git a/exp/kerokero/train.py b/exp/kerokero/train.py
--- a/exp/kerokero/train.py
+++ b/exp/kerokero/train.py
@@ -1,4 +1,5 @@
 import os
+import math
 from time import time
 import argparse
 import logging as log
@@ -11,7 +12,7 @@ import keras.losses
 import keras.metrics
 
 import config as cfg
-from k_util import averageDistance
+from k_util import averageDistance,generateData
 
 keras.losses.averageDistance=averageDistance
 keras.metrics.averageDistance=averageDistance
@@ -78,23 +79,29 @@ if args.load_model:
 
 log.info("loading data...")
 with np.load(args.data) as data:
-	trainImages=data["trainImages"]
-	trainLabels=data["trainLabels"]
-	testImages=data["testImages"]
-	testLabels=data["testLabels"]
+	trainImages=data["trainImages"].reshape((-1,224,224,1))
+	trainLabels=data["trainLabels"].reshape((-1,4,2))
+	testImages=data["testImages"].reshape((-1,224,224,1))
+	testLabels=data["testLabels"].reshape((-1,4,2))
 log.info("done")
 
+n=len(trainImages)
+k=round(n*0.9)
+n_=n-k
+(trainImages,valImages)=(np.float32(trainImages[:k]),np.float32(trainImages[k:]))
+(trainLabels,valLabels)=(np.float32(trainLabels[:k]),np.float32(trainLabels[k:]))
+
 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.reshape((-1,4,2)),
+model.fit_generator(
+	generateData(trainImages,trainLabels,batch_size=20),
 	epochs=args.epochs,
 	initial_epoch=args.initial_epoch,
-	batch_size=20,
-	validation_split=0.2,
+	steps_per_epoch=math.ceil(n_/20),
+	validation_data=generateData(valImages,valLabels,batch_size=20),
+	validation_steps=math.ceil(k/20),
 	callbacks=[tensorboard,checkpoint]
 )
 
-log.info(model.evaluate(testImages.reshape((-1,224,224,1)),testLabels.reshape((-1,4,2))))
+log.info(model.evaluate(testImages,testLabels))