What does the training accuracy plot of my convolution neural network (CNN) show?

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Hello everybody
the result of my CNN is shown in the picture attached. I'm wondering about the accuracy why it goes down and up during the training? is it normal or it should grow gradually? and what is the possible error that may I have on my net (or parameters)!! Additionally, whatever I change the training options; the test accuracy does not exceed 42% !!!
if true
Training on single CPU.
|=========================================================================================|
| Epoch | Iteration | Time Elapsed | Mini-batch | Mini-batch | Base Learning|
| | | (seconds) | Loss | Accuracy | Rate |
|=========================================================================================|
| 1 | 1 | 6.67 | 1.6277 | 0.00% | 1.00e-04 |
| 1 | 20 | 128.30 | 1.6677 | 25.00% | 1.00e-04 |
| 1 | 40 | 253.77 | 1.6505 | 50.00% | 1.00e-04 |
| 1 | 60 | 381.41 | 0.9331 | 87.50% | 1.00e-04 |
| 1 | 80 | 505.31 | 1.0754 | 25.00% | 1.00e-04 |
| 2 | 100 | 629.83 | 1.6579 | 12.50% | 1.00e-04 |
| 2 | 120 | 758.84 | 1.3724 | 62.50% | 1.00e-04 |
| 2 | 140 | 884.09 | 1.1539 | 50.00% | 1.00e-04 |
| 2 | 160 | 1028.53 | 1.1311 | 37.50% | 1.00e-04 |
| 2 | 180 | 1154.14 | 1.4353 | 37.50% | 1.00e-04 |
| 3 | 200 | 1277.55 | 0.9360 | 50.00% | 1.00e-04 |
| 3 | 220 | 1401.44 | 0.9559 | 50.00% | 1.00e-04 |
| 3 | 240 | 1525.49 | 1.6097 | 25.00% | 1.00e-04 |
| 3 | 260 | 1649.96 | 0.9116 | 62.50% | 1.00e-04 |
| 3 | 280 | 1774.19 | 1.0897 | 37.50% | 1.00e-04 |
| 4 | 300 | 1898.34 | 1.4818 | 12.50% | 1.00e-04 |
| 4 | 320 | 2022.42 | 1.1853 | 50.00% | 1.00e-04 |
| 4 | 340 | 2146.87 | 0.9665 | 62.50% | 1.00e-04 |
| 4 | 360 | 2272.24 | 1.1143 | 37.50% | 1.00e-04 |
| 4 | 380 | 2396.43 | 1.1264 | 37.50% | 1.00e-04 |
| 5 | 400 | 2522.21 | 1.5471 | 50.00% | 1.00e-04 |
| 5 | 420 | 2646.45 | 1.3815 | 50.00% | 1.00e-04 |
| 5 | 440 | 2776.98 | 0.7213 | 87.50% | 1.00e-04 |
| 5 | 460 | 2906.50 | 0.8455 | 87.50% | 1.00e-04 |
| 6 | 480 | 3033.40 | 1.7557 | 12.50% | 1.00e-04 |
| 6 | 500 | 3159.12 | 1.1510 | 50.00% | 1.00e-04 |
| 6 | 520 | 3290.33 | 1.0716 | 62.50% | 1.00e-04 |
| 6 | 540 | 3419.24 | 1.2187 | 37.50% | 1.00e-04 |
| 6 | 560 | 3545.82 | 1.3443 | 37.50% | 1.00e-04 |
| 7 | 580 | 3671.92 | 0.9136 | 50.00% | 1.00e-04 |
| 7 | 600 | 3796.45 | 0.8985 | 62.50% | 1.00e-04 |
| 7 | 620 | 3920.45 | 1.4416 | 37.50% | 1.00e-04 |
| 7 | 640 | 4051.54 | 0.9950 | 75.00% | 1.00e-04 |
| 7 | 660 | 4191.68 | 0.8132 | 75.00% | 1.00e-04 |
| 8 | 680 | 4328.36 | 1.3569 | 25.00% | 1.00e-04 |
| 8 | 700 | 4463.55 | 1.1009 | 50.00% | 1.00e-04 |
| 8 | 720 | 4593.56 | 1.0073 | 62.50% | 1.00e-04 |
| 8 | 740 | 4718.89 | 1.0589 | 50.00% | 1.00e-04 |
| 8 | 760 | 4843.50 | 0.9829 | 50.00% | 1.00e-04 |
| 9 | 780 | 4965.23 | 1.2858 | 62.50% | 1.00e-04 |
| 9 | 800 | 5086.95 | 1.4522 | 50.00% | 1.00e-04 |
| 9 | 820 | 5207.89 | 0.4955 | 100.00% | 1.00e-04 |
| 9 | 840 | 5328.95 | 0.7283 | 100.00% | 1.00e-04 |
| 10 | 860 | 5450.18 | 1.6487 | 37.50% | 1.00e-04 |
| 10 | 880 | 5570.79 | 0.8402 | 75.00% | 1.00e-04 |
| 10 | 900 | 5692.05 | 0.8969 | 62.50% | 1.00e-04 |
| 10 | 920 | 5812.29 | 1.1199 | 37.50% | 1.00e-04 |
| 10 | 940 | 5932.70 | 1.0859 | 50.00% | 1.00e-04 |
| 11 | 960 | 6053.34 | 0.7106 | 62.50% | 1.00e-04 |
| 11 | 980 | 6173.80 | 0.8470 | 50.00% | 1.00e-04 |
| 11 | 1000 | 6295.36 | 1.3543 | 25.00% | 1.00e-04 |
| 11 | 1020 | 6415.40 | 1.0594 | 50.00% | 1.00e-04 |
| 11 | 1040 | 6537.31 | 0.4968 | 75.00% | 1.00e-04 |
| 12 | 1060 | 6659.25 | 1.0452 | 50.00% | 1.00e-04 |
| 12 | 1080 | 6780.46 | 0.8746 | 62.50% | 1.00e-04 |
| 12 | 1100 | 6900.97 | 1.1169 | 50.00% | 1.00e-04 |
| 12 | 1120 | 7022.03 | 0.9600 | 50.00% | 1.00e-04 |
| 12 | 1140 | 7144.63 | 0.8063 | 50.00% | 1.00e-04 |
| 13 | 1160 | 7266.01 | 1.0481 | 75.00% | 1.00e-04 |
| 13 | 1180 | 7385.75 | 1.3504 | 50.00% | 1.00e-04 |
| 13 | 1200 | 7505.62 | 0.3157 | 100.00% | 1.00e-04 |
| 13 | 1220 | 7627.16 | 0.6529 | 87.50% | 1.00e-04 |
| 14 | 1240 | 7749.26 | 1.1844 | 62.50% | 1.00e-04 |
| 14 | 1260 | 7874.78 | 0.6447 | 75.00% | 1.00e-04 |
| 14 | 1280 | 7994.68 | 0.7824 | 62.50% | 1.00e-04 |
| 14 | 1300 | 8114.98 | 0.9300 | 62.50% | 1.00e-04 |
| 14 | 1320 | 8237.20 | 0.8984 | 62.50% | 1.00e-04 |
| 15 | 1340 | 8359.44 | 0.4070 | 75.00% | 1.00e-04 |
| 15 | 1360 | 8481.32 | 1.0424 | 62.50% | 1.00e-04 |
| 15 | 1380 | 8601.45 | 0.8956 | 50.00% | 1.00e-04 |
| 15 | 1400 | 8722.41 | 0.9647 | 62.50% | 1.00e-04 |
| 15 | 1420 | 8844.57 | 0.2415 | 100.00% | 1.00e-04 |
| 15 | 1425 | 8874.94 | 0.6794 | 62.50% | 1.00e-04 |
|=========================================================================================|
accuracy =
0.3787
end

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