Table 12 Training and validation accuracy and loss per epoch for hybrid model.

1

0.5974

0.6754

0.6815

0.5597

2

0.6914

0.5856

0.6810

0.5064

3

0.7059

0.5495

0.6792

0.4789

4

0.7203

0.5237

0.7254

0.4518

5

0.7387

0.5104

0.7184

0.4327

6

0.7471

0.4956

0.7188

0.4183

7

0.7551

0.4806

0.7182

0.4110

8

0.7596

0.4749

0.7192

0.4027

9

0.7618

0.4695

0.7199

0.3983

10

0.7625

0.4629

0.7208

0.3942

11

0.7615

0.4620

0.7212

0.3897

12

0.7653

0.4583

0.7217

0.3890

13

0.7665

0.4542

0.7282

0.3838

14

0.7657

0.4523

0.7294

0.3823

15

0.7685

0.4507

0.7317

0.3794

16

0.7723

0.4448

0.7336

0.3760

17

0.7712

0.4443

0.7340

0.3757

18

0.7719

0.4413

0.7350

0.3734

19

0.7736

0.4424

0.7370

0.3701

20

0.7742

0.4392

0.7377

0.3687

21

0.7724

0.4384

0.7377

0.3692

22

0.7736

0.4361

0.7382

0.3685

23

0.7747

0.4365

0.7398

0.3650

24

0.7735

0.4337

0.7399

0.3639

25

0.7763

0.4348

0.7408

0.3607

26

0.7762

0.4318

0.7414

0.3600

27

0.7749

0.4299

0.7415

0.3592

28

0.7737

0.4296

0.7415

0.3581

29

0.7754

0.4270

0.7416

0.3589

30

0.7776

0.4288

0.7430

0.3544