Change batch size and epochs for NCF benchmarks

Current batch size 160000 does not converge to the desired HR. So we decrease to 99k which is known to converge. Tested locally and got to 63.5 at epoch 7. Also decreasing number of epochs as I don't see any improvement after epoch 7-8.

official/recommendation/ncf_keras_benchmark.py

@@ -81,9 +81,9 @@ class KerasNCFRealData(KerasNCFBenchmarkBase):
     default_flags = {}
     default_flags['dataset'] = 'ml-20m'
     default_flags['num_gpus'] = 1
-    default_flags['train_epochs'] = 14
+    default_flags['train_epochs'] = 8
     default_flags['clean'] = True
-    default_flags['batch_size'] = 160000
+    default_flags['batch_size'] = 99000
     default_flags['learning_rate'] = 0.00382059
     default_flags['beta1'] = 0.783529
     default_flags['beta2'] = 0.909003
@@ -138,8 +138,8 @@ class KerasNCFSyntheticData(KerasNCFBenchmarkBase):
     default_flags = {}
     default_flags['dataset'] = 'ml-20m'
     default_flags['num_gpus'] = 1
-    default_flags['train_epochs'] = 14
-    default_flags['batch_size'] = 160000
+    default_flags['train_epochs'] = 8
+    default_flags['batch_size'] = 99000
     default_flags['learning_rate'] = 0.00382059
     default_flags['beta1'] = 0.783529
     default_flags['beta2'] = 0.909003