loss with epochs

Code/loss_visualization.py

@@ -3,7 +3,7 @@
 import matplotlib.pyplot as plt
 import re
 
-with open("loss.txt", "r") as f:
+with open("output_baselines_loss.txt", "r") as f:
     loss_file = f.read()
 
 pattern = r"\((\d+\.\d+)"

Code/train.py

@@ -46,6 +46,7 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 	for epoch in range(num_epochs):
 		#for param_tensor in model.state_dict():
 		#	print(param_tensor, "\t", model.state_dict()[param_tensor])
+		print("Epoche: " epoch)
 		index=0
 		for batch in train_dataloader:
 			if name[0] == "b":
@@ -110,7 +111,7 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 					#add mira 1 line
 					#new_labels_batch = new_labels_batch.to(torch.float64)
 
-					loss_2=loss_fct(logits.view(-1, 2).to("cuda"), new_labels_batch.view(-1).to("cuda")).to(torch.float32)
+					loss_2=loss_fct(logits.view(-1, 2).to("cuda"), new_labels_batch.view(-1).to("cuda"))#.to(torch.float32)
 					print("MixUp Loss: ", loss_2)
 					#update entire model
 					loss_2.backward()