单模态和多模态地址使用微调后的模型预测得到的结果与原生的不一致，ModelScope问题什么原因？

"{'scores': [0.49239251017570496, 0.500828742980957, 0.500383734703064]}
{'scores': [0.5252724289894104, 0.5078459978103638, 0.5178839564323425]},单模态和多模态地址使用微调后的模型预测得到的结果与原生的不一致，不知这个ModelScope问题是什么原因？

预测地址：
multi_modal_inputs = {
""source_sentence"": ['杭州余杭东方未来学校附近世纪华联商场(金家渡北苑店)'],
""first_sequence_gis"": [[[13159, 13295, 13136, 13157, 13158, 13291, 13294, 74505, 74713, 75387, 75389, 75411], [3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4], [3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4], [[1254, 1474, 1255, 1476], [1253, 1473, 1256, 1476], [1247, 1473, 1255, 1480], [1252, 1475, 1253, 1476], [1253, 1475, 1253, 1476], [1252, 1471, 1254, 1475], [1254, 1473, 1256, 1475], [1238, 1427, 1339, 1490], [1238, 1427, 1339, 1490], [1252, 1474, 1255, 1476], [1252, 1474, 1255, 1476], [1249, 1472, 1255, 1479]], [[24, 23, 15, 23], [24, 28, 15, 18], [31, 24, 22, 22], [43, 13, 37, 13], [43, 6, 35, 6], [31, 32, 22, 14], [19, 30, 9, 16], [24, 30, 15, 16], [24, 30, 15, 16], [29, 24, 20, 22], [28, 25, 19, 21], [31, 26, 22, 20]], ""120.08802231437534,30.343853313981505""]],
""sentences_to_compare"": [
'良渚街道金家渡北苑42号世纪华联超市(金家渡北苑店)',
'金家渡路金家渡中苑南区70幢金家渡中苑70幢',
'金家渡路140-142号附近家家福足道(金家渡店)'
],
""second_sequence_gis"": [
[[13083, 13081, 13084, 13085, 13131, 13134, 13136, 13147, 13148], [3, 3, 3, 3, 3, 3, 3, 3, 3], [3, 4, 4, 4, 4, 4, 4, 4, 4], [[1248, 1477, 1250, 1479], [1248, 1475, 1250, 1476], [1247, 1478, 1249, 1481], [1249, 1479, 1249, 1480], [1249, 1476, 1250, 1476], [1250, 1474, 1252, 1478], [1247, 1473, 1255, 1480], [1250, 1478, 1251, 1479], [1249, 1478, 1250, 1481]], [[30, 26, 21, 20], [32, 43, 23, 43], [33, 23, 23, 23], [31, 13, 22, 13], [25, 43, 16, 43], [20, 33, 10, 33], [26, 29, 17, 17], [18, 21, 8, 21], [26, 23, 17, 23]], ""120.08075205680345,30.34697777462197""],
[[13291, 13159, 13295, 74713, 75387, 75389, 75411], [3, 3, 3, 4, 4, 4, 4], [3, 4, 4, 4, 4, 4, 4], [[1252, 1471, 1254, 1475], [1254, 1474, 1255, 1476], [1253, 1473, 1256, 1476], [1238, 1427, 1339, 1490], [1252, 1474, 1255, 1476], [1252, 1474, 1255, 1476], [1249, 1472, 1255, 1479]], [[28, 28, 19, 18], [22, 16, 12, 16], [23, 24, 13, 22], [24, 30, 15, 16], [27, 20, 18, 20], [27, 21, 18, 21], [30, 24, 21, 22]], ""120.0872539617001,30.342783672056953""],
[[13291, 13290, 13294, 13295, 13298], [3, 3, 3, 3, 3], [3, 4, 4, 4, 4], [[1252, 1471, 1254, 1475], [1253, 1469, 1255, 1472], [1254, 1473, 1256, 1475], [1253, 1473, 1256, 1476], [1255, 1467, 1258, 1472]], [[32, 25, 23, 21], [26, 33, 17, 33], [21, 19, 11, 19], [25, 21, 16, 21], [21, 33, 11, 33]], ""120.08839673752281,30.34156156893651""]
]
}

# 单模态输入，只包括需要排序的文本
single_modal_inputs = {
    ""source_sentence"": ['杭州余杭东方未来学校附近世纪华联商场(金家渡北苑店)'],
    ""sentences_to_compare"": [
        '良渚街道金家渡北苑42号世纪华联超市(金家渡北苑店)',
        '金家渡路金家渡中苑南区70幢金家渡中苑70幢',
        '金家渡路140-142号附近家家福足道(金家渡店)'
        ]
    }          原生模型预测结果：

{'scores': [0.9997552633285522, 0.027718106284737587, 0.03500296175479889]}
{'scores': [0.9986912608146667, 0.0075200702995061874, 0.014017169363796711]}"