Keras Models Curves for Sequence Classification

1D CNN

#  history<-read_csv("/home/gab/dga-wb-r/results/cacic2021-test-only/attv4/History/results_ctu19b_awc-batch_size=1024-lstm_size=128-embedingdim=128-dropout=0.5-history.csv" ,col_types = cols())
history<-read_csv("/home/gab/dga-wb-r/results/cacic2021-test-only/results_history_test_cnn1d-augmented-ctu19-mccv-epochs=15-endgame-batch=1024-maxlen=1000-ctu19bplus-nb_filter=256-embedingdim=128-kernel_size=4-hidden_size=128-test-only.csv" ,col_types = cols())
#history<-history %>% reshape2::melt() %>% as.data.frame() %>% tibble::rowid_to_column()
loss_plot<-ggplot(history %>% filter(metric=="loss"))+
  facet_wrap(~data)+
  geom_point(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  geom_smooth(aes(x=epoch,y=value),se=FALSE,size=0.5,alpha=0.5,color='red')+
   xlim(0,60)+
  ylim(0,.5)+
  geom_line(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  ggdark::dark_theme_bw()+ labs(title="Loss values for Training and Validation sets (1DCNN)")
acc_plot<-ggplot(history %>% filter(metric=="accuracy"))+
  facet_wrap(~data)+
  geom_point(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  geom_smooth(aes(x=epoch,y=value),se=FALSE, size=0.5,alpha=0.5,color='red')+
  xlim(0,60)+
  ylim(0.5,1)+
  geom_line(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  ggdark::dark_theme_bw()+ labs(title="Accuracy values for Training and Validation sets (1DCNN) ")
gridExtra::grid.arrange(loss_plot,acc_plot,ncol=1)

LSTM

history<-read_csv("/home/gab/dga-wb-r/results/cacic2021-test-only/results_history_test_lstm-augmented-ctu19-mccv-epochs=15-endgame-batch=1024-maxlen=1000-ctu19bplus-test-only-embedingdim=64-lstm_size=32-dropout=0.1-test-only.csv" ,col_types = cols())
#history<-history %>% reshape2::melt() %>% as.data.frame() %>% tibble::rowid_to_column()
loss_plot<-ggplot(history %>% filter(metric=="loss"))+
  facet_wrap(~data)+
  geom_point(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  geom_smooth(aes(x=epoch,y=value),se=FALSE,size=0.5,alpha=0.5,color='red')+
   xlim(0,60)+
  ylim(0,.5)+
  geom_line(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  ggdark::dark_theme_bw()+ labs(title="Loss values for Training and Validation sets (LSTM)")
acc_plot<-ggplot(history %>% filter(metric=="accuracy"))+
  facet_wrap(~data)+
  geom_point(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  geom_smooth(aes(x=epoch,y=value),se=FALSE, size=0.5,alpha=0.5,color='red')+
  xlim(0,60)+
  ylim(0.5,1)+
  geom_line(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  ggdark::dark_theme_bw()+ labs(title="Accuracy values for Training and Validation sets (LSTM) ")
gridExtra::grid.arrange(loss_plot,acc_plot,ncol=1)

ATTENTION

 history<-read_csv("/home/gab/dga-wb-r/results/cacic2021-test-only/attv4/History/results_ctu19b_awc-batch_size=1024-lstm_size=128-embedingdim=128-dropout=0.5-history.csv" ,col_types = cols())
history_val<-history   %>% tibble::rowid_to_column() %>% select(rowid,loss,val_loss) 
history_val<-history_val %>% reshape2::melt(id.vars="rowid") %>% mutate(data=ifelse(variable=="loss","training","validation"),variable='loss') %>% rename(epoch='rowid',metric='variable')
history_acc<-history   %>% tibble::rowid_to_column() %>% select(rowid,acc,val_acc) 
history_acc<-history_acc %>% reshape2::melt(id.vars="rowid") %>% mutate(data=ifelse(variable=="acc","training","validation"),variable='accuracy') %>% rename(epoch='rowid',metric='variable')
history<-rbind(history_acc,history_val)
loss_plot<-ggplot(history %>% filter(metric=="loss"))+
  facet_wrap(~data)+
  geom_point(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  geom_smooth(aes(x=epoch,y=value),se=FALSE,size=0.5,alpha=0.5,color='red')+
  xlim(0,60)+
  ylim(0,.5)+
  geom_line(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  ggdark::dark_theme_bw()+ labs(title="Loss values for Training and Validation sets (ATTE )")
acc_plot<-ggplot(history %>% filter(metric=="accuracy"))+
  facet_wrap(~data)+
  geom_point(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  geom_smooth(aes(x=epoch,y=value),se=FALSE, size=0.5,alpha=0.5,color='red')+
  xlim(0,60)+
  ylim(0.5,1)+
  geom_line(aes(x=epoch,y=value),col='orange',alpha=0.9)+
  ggdark::dark_theme_bw()+ labs(title="Accuracy values for Training and Validation sets (ATTE )")
gridExtra::grid.arrange(loss_plot,acc_plot,ncol=1)