Name errorが解決できません

前提・実現したいこと

kerasを用いたニューラルネットワークで、学習の結果を逐次histを使って記録していきたいのですが、name errorが出てきてしまいます。

発生している問題・エラーメッセージ

 File "/home/.../hoge.py", line 65, in <module>
    hist_acc_t = hist_acc_t + hist.history['acc']
NameError: name 'hist' is not defined

該当のソースコード

python
1data = pd.read_csv('SPSS.csv', sep=",", header=0)
2
3train_size = 0.7
4N_validation = 0.1
5
6X = DataFrame(data.drop("hoge_history", axis=1))
7
8Y = DataFrame(data["hoge_history"])
9
10X_train, X_test, Y_train, Y_test = \
11    train_test_split(X, Y, train_size=train_size)
12X_train, X_validation, Y_train, Y_validation = \
13    train_test_split(X_train, Y_train, train_size=N_validation)
14
15#モデル設定
16n_in = 357
17n_hidden = 50
18n_out = 1
19
20model = Sequential()
21
22model.add(Dense(n_hidden, input_dim=n_in))
23model.add(Activation('sigmoid'))
24
25model.add(Dense(n_out))
26model.add(Activation('sigmoid'))
27
28model.compile(loss='binary_crossentropy',
29              optimizer=SGD(lr=0.1),
30              metrics=['accuracy'])
31
32epochs = 200
33batch_size = 4
34
35hist_acc_t = hist_acc_v = hist_loss_t = hist_loss_v = []
36max_epochs = 1000 # 1000 エポックまで学習させる
37ep_learn_interval = 50 # 50 エポック毎にグラフ表示・ファイル書出
38
39def learn_body():
40    global hist_acc_t, hist_acc_v, hist_loss_t, hist_loss_v, hist, ep_num
41    for i in range(max_epochs):
42        ep_num = i + 1  # type: int
43        if ep_num % ep_learn_interval == 0:
44            hist = model.fit(X_train, Y_train, batch_size=batch_size,
45                epochs=ep_num - last_write_epoch,
46                validation_data=(X_validation, Y_validation), verbose=2)
47
48hist_acc_t = hist_acc_t + hist.history['acc']
49hist_acc_v = hist_acc_v + hist.history['val_acc']
50hist_loss_t = hist_loss_t + hist.history['loss']
51hist_loss_v = hist_loss_v + hist.history['val_loss']
52last_write_epoch = ep_num
53
54#学習の進み具合を可視化
55
56acc = hist.history['acc']
57loss = hist.history['loss']
58
59index = ['acc_t', 'acc_v', 'loss_t', 'loss_v']
60l = [hist_acc_t, hist_acc_v, hist_loss_t, hist_loss_v]
61
62with open('honyahonya.csv', 'w') as f:
63    w = csv.writer(f)
64    for i, row in zip(index, l):
65        w.writerow([i] + row)
66
67
68def plot_acc():
69
70def plot_loss():
71
72plot_acc()
73plot_loss()