def on_epoch_end(self, epoch, logs=None):
logs = logs or {}
predict_result = self.model.predict(
x=[self.index, self.e1_pos, self.e2_pos, self.relation_arr])
f1_score = get_marco_f1(predict_result, self.result)
self.save_best(f1_score)
logs["f1_score"] = f1_score
def on_epoch_end(self, epoch, logs=None):
logs = logs or {}
predict_result = self.model.predict(
x=[self.index, self.pos1_index, self.pos2_index, self.test_pos])
f1_score = get_marco_f1(predict_result, self.result)
self.save_best(f1_score)
logs["f1_score"] = f1_score
def on_epoch_end(self, epoch, logs=None):
logs = logs or {}
predict_result = self.model.predict(x=[
self.google_index, self.fasttext_index, self.relative_pos1,
self.relative_pos2, self.e1_pos, self.e2_pos
])
f1_score = get_marco_f1(predict_result, self.result)
logs["f1_score"] = f1_score
self.save_best(f1_score)