gensimのdoc2vecでlossを取りたい

前提・実現したいこと

gensimのdoc2vecでモデルを作成しています。
epoch毎のlossを取りたいのですが、running_training_loss が常にゼロです。。

どのようにして、lossの履歴を取ればいいでしょうか？
モデルの最適化の為に、loss図を作成したく。

結果

EPOCH - 1 : training on 1029767 raw words (890423 effective words) took 12.2s, 72703 effective words/s
loss= 0.0
Loss after epoch 0: 0.0

該当のソースコード

class callback(CallbackAny2Vec):
#'''Callback to print loss after each epoch.'''

def __init__(self):
	self.epoch = 0
	self.loss_to_be_subed = 0

def on_epoch_end(self, model):
	loss = model.running_training_loss
	print("loss=",loss)
	loss_now = loss - self.loss_to_be_subed
	self.loss_to_be_subed = loss
	print('Loss after epoch {}: {}'.format(self.epoch, loss_now))
	self.epoch += 1

model = Doc2Vec(documents, vector_size=300, window=5, min_count=1, workers=4,epochs=25,dbow_words=1,compute_loss=True,callbacks=[callback()])

python3
1#-*- encoding: utf-8 -*-
2################################################################
3# 2019.12.24 K.Tearda
4# doc2vec で学習
5# https://qiita.com/asian373asian/items/1be1bec7f2297b8326cf
6################################################################
7import os
8import logging
9import sys
10import numpy as np
11from datetime import datetime
12from gensim.models.doc2vec import Doc2Vec, TaggedDocument
13from gensim.models.callbacks import CallbackAny2Vec
14
15class callback(CallbackAny2Vec):
16	#'''Callback to print loss after each epoch.'''
17
18	def __init__(self):
19		self.epoch = 0
20		self.loss_to_be_subed = 0
21
22	def on_epoch_end(self, model):
23		loss = model.running_training_loss
24		print("loss=",loss)
25		#loss = model.get_latest_training_loss()
26		loss_now = loss - self.loss_to_be_subed
27		self.loss_to_be_subed = loss
28		print('Loss after epoch {}: {}'.format(self.epoch, loss_now))
29		self.epoch += 1
30
31###################### entry point
32argv=sys.argv
33debug="on"
34print("START: "+" ".join(argv),datetime.now())
35
36logging.basicConfig(format="%(asctime)s : %(levelname)s : %(message)s",level=logging.INFO)
37DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
38
39artistNo=np.load('artistNo.npy',allow_pickle=True)
40sentences=np.load('sentences.npy',allow_pickle=True)
41
42documents = [TaggedDocument(doc, [i]) for i, doc in sentences]
43
44model = Doc2Vec(documents, vector_size=300, window=5, min_count=1, workers=4,epochs=25,dbow_words=1,compute_loss=True,callbacks=[callback()])
45
46# モデルのセーブ
47model.save("doc2vec_gensim_songs.bin")
48
49print("END: ",argv[0],datetime.now())
50