Deep learning 如何微调HuggingFace Transformer XL模型以生成文本&；机器翻译？

我有一种机器翻译任务，我必须把英语句子翻译成汉英英语句子。我试图使用预先训练好的Transformer XL模型，在自定义数据集上对其进行微调。这是我的密码：

import pandas as pd
import tensorflow as tf
from transformers import TransfoXLTokenizer
from transformers import TFTransfoXLModel
import numpy as np
from sklearn.model_selection import train_test_split

#Loading data
dataFrame = pd.read_csv("data.csv")
dataFrame.head(3)

#-----Output 1-----

#Splitting Dataset
X = dataFrame['English']
Y = dataFrame['Hinglish']
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.2, random_state = 42)

#Tokenization
tokenizer = TransfoXLTokenizer.from_pretrained('transfo-xl-wt103')

tokenizer.pad_token = tokenizer.eos_token

XTrainEncodings = tokenizer(X_train.to_list(),  max_length = 150, padding = True)
XTestEncodings = tokenizer(X_test.to_list(), max_length = 150, padding = True)
YTrainEncodings = tokenizer(Y_train.to_list(), max_length = 150, padding = True)
YTestEncodings = tokenizer(Y_test.to_list(), max_length = 150, padding = True)
print("XTrainEncodings : ", XTrainEncodings)
print("YTrainEncodings : ", YTrainEncodings)

#-----Output 2-----

#Converting to Tensors
X_train = tf.data.Dataset.from_tensor_slices((dict(XTrainEncodings), (dict(YTrainEncodings))))
X_test = tf.data.Dataset.from_tensor_slices((dict(XTestEncodings), (dict(YTestEncodings))))
print(X_train)

#-----Output 3-----

#Fine Tuning
model = TFTransfoXLModel.from_pretrained('transfo-xl-wt103')

optimizer = tf.keras.optimizers.Adam(learning_rate = 5e-5)
model.compile(optimizer = optimizer, loss = tf.losses.SparseCategoricalCrossentropy(), metrics = ['accuracy'])

history = model.fit(X_train.batch(1), epochs = 2, batch_size = 1, validation_data = X_test.batch(1))

输出：

-----Output 1-----

    English                     Hinglish
How are you ?                Tum kaise ho ?
I am fine.                  Main theek hoon
......

-----Output 2-----
XTrainEncodings :  {'input_ids': [[4241, 0, 0, 0, 0, 0], [4827, 37, 304, 788, 0, 0],....
YTrainEncodings :  {'input_ids': [[13762, 0, 0, 0, 0], [71271, 24, 33289, 788, 0],....

-----Output 3-----
<TensorSliceDataset shapes: ({input_ids: (6,)}, {input_ids: (5,)}), types: ({input_ids: tf.int32}, {input_ids: tf.int32})>

请帮我找出原因并解决错误。此外，我想知道我是否遵循正确的方法来完成我的任务，或者是否有其他更好的方法。因为我对深度学习还不熟悉，所以我对此不确定。谢谢

ValueError: in user code:

    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:805 train_function  *
        return step_function(self, iterator)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:795 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:1259 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:2730 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:3417 _call_for_each_replica
        return fn(*args, **kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:788 run_step  **
        outputs = model.train_step(data)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:758 train_step
        self.compiled_metrics.update_state(y, y_pred, sample_weight)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/compile_utils.py:387 update_state
        self.build(y_pred, y_true)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/compile_utils.py:318 build
        self._metrics, y_true, y_pred)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/nest.py:1163 map_structure_up_to
        **kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/nest.py:1245 map_structure_with_tuple_paths_up_to
        expand_composites=expand_composites)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/nest.py:878 assert_shallow_structure
        input_length=len(input_tree), shallow_length=len(shallow_tree)))

    ValueError: The two structures don't have the same sequence length. Input structure has length 3, while shallow structure has length 2.