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)