fix epoch

SuperTagger/SuperTagger.py

@@ -236,21 +236,21 @@ class SuperTagger:
                 eval_accuracy, eval_loss, nb_eval_steps = self.__eval_epoch(validation_dataloader)
 
             print("")
-            print(f'Epoch: {epoch_i:02} | Epoch Time: {training_time}')
+            print(f'Epoch: {epoch_i+1:02} | Epoch Time: {training_time}')
             print(f'\tTrain Loss: {epoch_loss:.3f} | Train Acc: {epoch_acc * 100:.2f}%')
             if validation_rate > 0.0:
                 print(f'\tVal Loss: {eval_loss:.3f} | Val Acc: {eval_accuracy * 100:.2f}%')
 
             if tensorboard:
                 writer.add_scalars(f'Accuracy', {
-                    'Train': epoch_acc}, epoch_i)
+                    'Train': epoch_acc}, epoch_i+1)
                 writer.add_scalars(f'Loss', {
-                    'Train': epoch_loss}, epoch_i)
+                    'Train': epoch_loss}, epoch_i+1)
                 if validation_rate > 0.0:
                     writer.add_scalars(f'Accuracy', {
-                        'Validation': eval_accuracy}, epoch_i)
+                        'Validation': eval_accuracy}, epoch_i+1)
                     writer.add_scalars(f'Loss', {
-                        'Validation': eval_loss}, epoch_i)
+                        'Validation': eval_loss}, epoch_i+1)
 
             self.epoch_i += 1
 

train.py

@@ -4,7 +4,7 @@ from SuperTagger.Utils.helpers import read_csv_pgbar, load_obj
 #### DATA ####
 file_path = 'Datasets/m2_dataset.csv'
 
-df = read_csv_pgbar(file_path,1000)
+df = read_csv_pgbar(file_path,100)
 
 texts = df['X'].tolist()
 tags = df['Y1'].tolist()