Table 7. Performance metrics.

Expt.	Model	Accuracy	Precision	Recall	F1-score	Training time
I	Linear SVC	0.82	0.76	0.77	0.76	3 min 5 s
	Support vector	0.85	0.75	0.82	0.77	10 min 44 s
	Decision tree	0.72	0.64	0.64	0.64	9.43 s
	Random forest	0.84	0.69	0.85	0.73	19.3 s
	Logistic regression	0.84	0.78	0.78	0.78	10.7 s
	Multi-layer perceptron	0.86	0.80	0.82	0.81	2 min 14 s
	DistilBERT	0.84	0.82	0.76	0.78	1 min 43 s
II	Linear SVC	0.83	0.79	0.77	0.78	1 min 43 s
	Support vector	0.85	0.80	0.80	0.80	13.4 s
	Decision tree	0.71	0.62	0.61	0.62	1.52 s
	Random forest	0.83	0.69	0.84	0.72	5.47 s
	Logistic regression	0.81	0.79	0.75	0.77	0.53 s
	Multi-layer perceptron	0.85	0.78	0.8	0.79	15.8 s
III	Linear SVC	0.83	0.80	0.77	0.78	6.01 s
	Support vector	0.87	0.82	0.83	0.82	10.5 s
	Decision tree	0.74	0.64	0.65	0.65	4.2 s
	Random forest	0.82	0.67	0.83	0.70	16.8 s
	Logistic regression	0.82	0.80	0.76	0.77	0.33 s
	Multi-layer perceptron	0.86	0.78	0.82	0.80	8.79 s