why two different mini-batch Accuracy in CNN

I am trying train a CNN.GPU device is Nvidia 1050.

My code

           train_data_total=img;
           label_4=YTrain;

          layers_first = [imageInputLayer([32 32 3],'Normalization','none');
          convolution2dLayer(5,130);
          reluLayer();
          maxPooling2dLayer(2,'Stride',2);

          convolution2dLayer(5,180);
          reluLayer();
          maxPooling2dLayer(2,'Stride',2);   

          fullyConnectedLayer(256);
          reluLayer();
          fullyConnectedLayer(2);
          softmaxLayer();
          classificationLayer()];

      opts_first = trainingOptions('sgdm','MiniBatchSize',256,'MaxEpochs',70 ...
          ,'InitialLearnRate',0.01,'Momentum',0,'Shuffle','once');

      train_data_total=imresize(train_data_total,[32 32]);

      net_first = trainNetwork(train_data_total,label_4,layers_first,opts_first);

      YTrain_output1=classify(net_first,train_data_total);

      train_accuracy1 = sum(YTrain_output1 == label_4)/numel(label_4)

My question is why Mini-batch Accuracy is around 50%.

And another computer using the same code and same input has Mini-batch Accuracy is around 98%.

Anyone has an idea of this

[Arthur Chien]

Another computer GPU Nvidia gt730.

[Joss Knight]

Are you using MATLAB R2016b?

[Arthur Chien]

I am using Matlab R2016a

[Joss Knight]

Then you need to install the patch.

Answer 1

[Joss Knight]

You need to install the patch.

[Arthur Chien]

This help. Thank you.

[Joss Knight]

Please accept the answer.

[shefali saxena]

hello sir

i am using Matlab R2017b

I am facing the same problem when traing CNN for ECG signals

My Mini-batch Accuracy is around 50%. and Mini Batch loss is Fixed at 0.69xx.

how can i resolve this problem ???

Training on single CPU.

|=======================================================================|

| Epoch | Iteration | Time Elapsed | Mini-batch | Mini-batch | Base Learning|

| | | (seconds) | Loss | Accuracy | Rate |

|=======================================================================|

| 1 | 1 | 0.72 | 0.6930 | 70.00% | 0.0010 |

| 4 | 320 | 11.36 | 0.6931 | 50.00% | 0.0010 |

| 8 | 640 | 21.76 | 0.6929 | 70.00% | 0.0010 |

| 12 | 960 | 32.12 | 0.6937 | 40.00% | 0.0010 |

| 16 | 1280 | 42.50 | 0.6932 | 50.00% | 0.0010 |

| 20 | 1600 | 53.04 | 0.6932 | 50.00% | 0.0010 |

| 23 | 1920 | 63.60 | 0.6930 | 50.00% | 0.0010 |

| 27 | 2240 | 74.73 | 0.6929 | 70.00% | 0.0010 |

| 31 | 2560 | 85.56 | 0.6932 | 50.00% | 0.0010 |

| 35 | 2880 | 96.81 | 0.6929 | 80.00% | 0.0010 |

| 39 | 3200 | 107.51 | 0.6930 | 60.00% | 0.0010 |

| 42 | 3520 | 118.29 | 0.6938 | 40.00% | 0.0010 |

| 46 | 3840 | 129.85 | 0.6933 | 30.00% | 0.0010 |

| 50 | 4160 | 140.92 | 0.6946 | 30.00% | 0.0010 |

| 54 | 4480 | 151.81 | 0.6928 | 60.00% | 0.0010 |

| 58 | 4800 | 163.14 | 0.6936 | 30.00% | 0.0010 |

| 61 | 5120 | 174.09 | 0.6932 | 50.00% | 0.0010 |

| 65 | 5440 | 184.38 | 0.6933 | 40.00% | 0.0010 |

| 69 | 5760 | 194.80 | 0.6928 | 60.00% | 0.0010 |

| 73 | 6080 | 205.18 | 0.6938 | 40.00% | 0.0010 |

| 77 | 6400 | 215.87 | 0.6931 | 60.00% | 0.0010 |

| 80 | 6720 | 227.45 | 0.6934 | 30.00% | 0.0010 |

| 84 | 7040 | 239.33 | 0.6932 | 50.00% | 0.0010 |

| 88 | 7360 | 250.64 | 0.6930 | 70.00% | 0.0010 |

| 92 | 7680 | 261.30 | 0.6931 | 50.00% | 0.0010 |

| 96 | 8000 | 271.53 | 0.6931 | 60.00% | 0.0010 |

| 100 | 8320 | 282.09 | 0.6935 | 40.00% | 0.0010 |

| 100 | 8400 | 284.69 | 0.6937 | 30.00% | 0.0010 |

|=======================================================================|

accuracy = 0.5000

please help !!!!