Table 11 Comparison results of best model on test set.

From: Development of an automated transformer-based text analysis framework for monitoring fire door defects in buildings

Category

Class1

Class2

Class3

Class4

Class5

Class6

Class7

Class8

Average

Proposed method

F1 score

92.13

87.29

78.17

82.89

80.17

96.66

98.43

67.81

85.44

Accuracy

91.55

87.22

75.84

81.78

79.49

96.16

98.27

67.74

84.76

ANN

F1 score

86.94

82.51

44.38

79.7

78.97

95.46

97.67

63.41

78.63

Accuracy

86.34

83.53

45.25

76.92

75.24

94.7

96.95

66.41

78.17

SVM

F1 score

87.26

84.43

45.73

81.08

76.92

95.53

96.62

65.66

79.15

Accuracy

86.81

83.19

44.44

78.97

76.32

95.45

95.04

66.47

78.34

DT

F1 score

81.34

82.52

43.32

78.75

78.3

95.72

94.85

65.33

77.52

Accuracy

80.5

84.49

45.19

77.19

77.83

92.68

96.37

64.9

77.39

RF

F1 score

89.17

85.96

43.31

78.9

75.44

92.13

95.24

63.16

77.91

Accuracy

87.65

85.84

45.14

79.82

77.24

94.44

94.04

65.63

78.73

LR

F1 score

87.37

84.35

47.04

78.78

79.33

91.72

94.45

66.42

78.68

Accuracy

88.03

83.05

42.16

78.02

75.52

91.33

94.16

66.72

77.37

1D CNN

F1 score

89.75

83.99

56.18

82.1

78.27

94.7

94.65

64.44

80.51

Accuracy

89.06

84.6

54.8

78.07

75.57

93.13

94.3

65.02

79.32

LSTM

F1 score

89.28

84.87

57.56

81.9

79.53

92.42

96.52

65.02

80.89

Accuracy

86.97

85.61

53.49

77.88

77.96

92.31

96.47

66.51

79.65