FAQ
1. Set learning rate and use earlystopping
import deepmatch
from tensorflow.python.keras.optimizers import Adam,Adagrad
from tensorflow.python.keras.callbacks import EarlyStopping
model = deepmatch.models.FM(user_feature_columns,item_feature_columns)
model.compile(Adagrad(0.01),'binary_crossentropy',metrics=['binary_crossentropy'])
es = EarlyStopping(monitor='val_binary_crossentropy')
history = model.fit(model_input, data[target].values,batch_size=256, epochs=10, verbose=2, validation_split=0.2,callbacks=[es] )Last updated