diff --git a/Makefile b/Makefile
index 4bdd0f6..740ca4e 100644
--- a/Makefile
+++ b/Makefile
@@ -65,10 +65,10 @@ $(BUILDDIR)/mnist_%.o: $(MNIST_SRCDIR)/%.c $(MNIST_SRCDIR)/include/%.h
 #
 cnn: $(BUILDDIR)/cnn-main;
 
-$(BUILDDIR)/cnn-main: $(CNN_SRCDIR)/main.c $(BUILDDIR)/cnn_train.o $(BUILDDIR)/cnn_cnn.o $(BUILDDIR)/cnn_creation.o $(BUILDDIR)/cnn_initialisation.o $(BUILDDIR)/cnn_make.o $(BUILDDIR)/cnn_neuron_io.o $(BUILDDIR)/cnn_function.o  $(BUILDDIR)/cnn_utils.o $(BUILDDIR)/cnn_free.o $(BUILDDIR)/cnn_convolution.o $(BUILDDIR)/cnn_backpropagation.o $(BUILDDIR)/colors.o $(BUILDDIR)/mnist.o
+$(BUILDDIR)/cnn-main: $(CNN_SRCDIR)/main.c $(BUILDDIR)/cnn_train.o $(BUILDDIR)/cnn_cnn.o $(BUILDDIR)/cnn_creation.o $(BUILDDIR)/cnn_initialisation.o $(BUILDDIR)/cnn_make.o $(BUILDDIR)/cnn_neuron_io.o $(BUILDDIR)/cnn_function.o  $(BUILDDIR)/cnn_utils.o $(BUILDDIR)/cnn_update.o $(BUILDDIR)/cnn_free.o $(BUILDDIR)/cnn_convolution.o $(BUILDDIR)/cnn_backpropagation.o $(BUILDDIR)/colors.o $(BUILDDIR)/mnist.o
 	$(CC)     $^ -o $@  $(CFLAGS)
 
-$(BUILDDIR)/cnn-main-cuda: $(BUILDDIR)/cnn_main.o $(BUILDDIR)/cnn_train.o $(BUILDDIR)/cnn_cnn.o $(BUILDDIR)/cnn_creation.o $(BUILDDIR)/cnn_initialisation.o $(BUILDDIR)/cnn_make.o $(BUILDDIR)/cnn_neuron_io.o $(BUILDDIR)/cnn_function.o  $(BUILDDIR)/cnn_utils.o $(BUILDDIR)/cnn_free.o $(BUILDDIR)/cnn_cuda_convolution.o $(BUILDDIR)/cnn_backpropagation.o $(BUILDDIR)/cuda_utils.o $(BUILDDIR)/colors.o $(BUILDDIR)/mnist.o
+$(BUILDDIR)/cnn-main-cuda: $(BUILDDIR)/cnn_main.o $(BUILDDIR)/cnn_train.o $(BUILDDIR)/cnn_cnn.o $(BUILDDIR)/cnn_creation.o $(BUILDDIR)/cnn_initialisation.o $(BUILDDIR)/cnn_make.o $(BUILDDIR)/cnn_neuron_io.o $(BUILDDIR)/cnn_function.o  $(BUILDDIR)/cnn_utils.o $(BUILDDIR)/cnn_update.o $(BUILDDIR)/cnn_free.o $(BUILDDIR)/cnn_cuda_convolution.o $(BUILDDIR)/cnn_backpropagation.o $(BUILDDIR)/cuda_utils.o $(BUILDDIR)/colors.o $(BUILDDIR)/mnist.o
 	$(NVCC)  $(NVCCFLAGS)  $^ -o $@
 
 $(BUILDDIR)/cnn_%.o: $(CNN_SRCDIR)/%.c $(CNN_SRCDIR)/include/%.h
diff --git a/src/cnn/train.c b/src/cnn/train.c
index 22b4c07..00067ed 100644
--- a/src/cnn/train.c
+++ b/src/cnn/train.c
@@ -54,7 +54,6 @@ void* train_thread(void* parameters) {
             maxi = indice_max(network->input[network->size-1][0][0], 10);
             backward_propagation(network, labels[i]);
             if (cpt==16) { // Update the network
-                printf("a\n");
                 update_weights(network);
                 update_bias(network);
                 cpt = 0;
@@ -78,9 +77,9 @@ void train(int dataset_type, char* images_file, char* labels_file, char* data_di
     int input_dim = -1;
     int input_depth = -1;
     float accuracy;
+    float current_accuracy;
 
     int nb_images_total;
-    int nb_remaining_images;
 
     int*** images;
     unsigned int* labels;
@@ -109,6 +108,7 @@ void train(int dataset_type, char* images_file, char* labels_file, char* data_di
     Network* network = create_network_lenet5(0, 0, TANH, GLOROT, input_dim, input_depth);
 
     #ifdef USE_MULTITHREADING
+    int nb_remaining_images; // Nombre d'images restantes à lancer pour une série de threads
     // Récupération du nombre de threads disponibles
     int nb_threads = get_nprocs();
     pthread_t *tid = (pthread_t*)malloc(nb_threads * sizeof(pthread_t));
@@ -168,9 +168,9 @@ void train(int dataset_type, char* images_file, char* labels_file, char* data_di
         // et donnera donc des résultats différents sur les mêmes images.
         accuracy = 0.;
         for (int j=0; j < nb_images_total / BATCHES; j++) {
+            #ifdef USE_MULTITHREADING
             nb_remaining_images = BATCHES;
 
-            #ifdef USE_MULTITHREADING
             for (int k=0; k < nb_threads; k++) {
                 if (k == nb_threads-1) {
                     train_parameters[k]->nb_images = nb_remaining_images;
@@ -189,18 +189,20 @@ void train(int dataset_type, char* images_file, char* labels_file, char* data_di
                 // TODO patch_network(network, train_parameters[k]->network, train_parameters[k]->nb_images);
                 free_network(train_parameters[k]->network);
             }
-            printf("\rThreads [%d]\tÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: %0.1f%%", nb_threads, i, epochs, BATCHES*(j+1), nb_images_total, accuracy*100);
+            current_accuracy = accuracy * nb_images_total/(j*BATCHES);
+            printf("\rThreads [%d]\tÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: "YELLOW"%0.1f%%"RESET"\t", nb_threads, i, epochs, BATCHES*(j+1), nb_images_total, current_accuracy*100);
             #else
             train_params->start = j*BATCHES;
             train_thread((void*)train_params);
             accuracy += train_params->accuracy / (float) nb_images_total;
-            printf("\rÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: %0.1f%%", i, epochs, BATCHES*(j+1), nb_images_total, accuracy*100);
+            current_accuracy = accuracy * nb_images_total/(j*BATCHES);
+            printf("\rÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: "YELLOW"%0.1f%%"RESET"\t", i, epochs, BATCHES*(j+1), nb_images_total, current_accuracy*100);
             #endif
         }
         #ifdef USE_MULTITHREADING
-        printf("\rThreads [%d]\tÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: %0.1f%%\n", nb_threads, i, epochs, nb_images_total, nb_images_total, accuracy*100);
+        printf("\rThreads [%d]\tÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: "GREEN"%0.1f%%"RESET"\t\n", nb_threads, i, epochs, nb_images_total, nb_images_total, accuracy*100);
         #else
-        printf("\rÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: %0.1f%%\n", i, epochs, nb_images_total, nb_images_total, accuracy*100);
+        printf("\rÉpoque [%d/%d]\tImage [%d/%d]\tAccuracy: "GREEN"%0.1f%%"RESET"\t\n", i, epochs, nb_images_total, nb_images_total, accuracy*100);
         #endif
         write_network(out, network);
     }