diff --git a/Pilot3/P3B6/p3b6.py b/Pilot3/P3B6/p3b6.py
index 4bc52c6c..c9bda47f 100644
--- a/Pilot3/P3B6/p3b6.py
+++ b/Pilot3/P3B6/p3b6.py
@@ -10,6 +10,13 @@
     {"name": "weight_decay", "action": "store", "type": float},
     {"name": "grad_clip", "action": "store", "type": int},
     {"name": "unrolled", "action": "store", "type": candle.str2bool},
+    {"name": "device", "action": "store", "type": str},
+    {"name": "num_train_samples", "action": "store", "type": int},
+    {"name": "num_valid_samples", "action": "store", "type": int},
+    {"name": "num_test_samples", "action": "store", "type": int},
+    {"name": "num_classes", "action": "store", "type": int},
+    {"name": "eps", "action": "store", "type": float},
+
 ]
 
 required = [
diff --git a/Pilot3/P3B7/p3b7.py b/Pilot3/P3B7/p3b7.py
index f0658d77..51dd7dad 100644
--- a/Pilot3/P3B7/p3b7.py
+++ b/Pilot3/P3B7/p3b7.py
@@ -11,6 +11,14 @@
     {"name": "grad_clip", "action": "store", "type": int},
     {"name": "unrolled", "action": "store", "type": candle.str2bool},
     {"name": "use_synthetic_data", "action": "store", "type": candle.str2bool},
+    {"name": "eps", "action": "store", "type": float},
+    {"name": "device", "action": "store", "type": str},
+    {"name": "embed_dim", "action": "store", "type": int},
+    {"name": "n_filters", "action": "store", "type": int},
+    {"name": "kernel1", "action": "store", "type": int},
+    {"name": "kernel2", "action": "store", "type": int},
+    {"name": "kernel3", "action": "store", "type": int},
+
 ]
 
 required = [
diff --git a/Pilot3/P3B8/default_model.txt b/Pilot3/P3B8/default_model.txt
index b96f696b..0470bb50 100644
--- a/Pilot3/P3B8/default_model.txt
+++ b/Pilot3/P3B8/default_model.txt
@@ -4,7 +4,7 @@ learning_rate = 2e-5
 eps = 1e-8
 weight_decay = 0.0
 batch_size = 10
-num_epochs = 10
+epochs = 10
 rng_seed = 13
 num_train_samples = 10000
 num_valid_samples = 10000
diff --git a/Pilot3/P3B8/p3b8.py b/Pilot3/P3B8/p3b8.py
index 2faebcd7..d2472104 100644
--- a/Pilot3/P3B8/p3b8.py
+++ b/Pilot3/P3B8/p3b8.py
@@ -10,6 +10,12 @@
     {"name": "weight_decay", "action": "store", "type": float},
     {"name": "grad_clip", "action": "store", "type": int},
     {"name": "unrolled", "action": "store", "type": candle.str2bool},
+    {"name": "device", "action": "store", "type": str},
+    {"name": "num_train_samples", "action": "store", "type": int},
+    {"name": "num_valid_samples", "action": "store", "type": int},
+    {"name": "num_test_samples", "action": "store", "type": int},
+    {"name": "num_classes", "action": "store", "type": int},
+    {"name": "eps", "action": "store", "type": float},
 ]
 
 required = [
@@ -17,7 +23,7 @@
     "weight_decay",
     "rng_seed",
     "batch_size",
-    "num_epochs",
+    "epochs",
 ]
 
 
diff --git a/Pilot3/P3B8/p3b8_baseline_pytorch.py b/Pilot3/P3B8/p3b8_baseline_pytorch.py
index 45f24bd5..647b3e42 100644
--- a/Pilot3/P3B8/p3b8_baseline_pytorch.py
+++ b/Pilot3/P3B8/p3b8_baseline_pytorch.py
@@ -90,7 +90,7 @@ def validate(dataloader, model, args, device, epoch):
         for idx, batch in enumerate(dataloader):
 
             input_ids = batch["tokens"].to(device)
-            labels = batch["label"].to(args.device)
+            labels = batch["label"].to(device)
 
             output = model(input_ids, labels=labels)
 
@@ -137,7 +137,7 @@ def run(args):
     optimizer = torch.optim.Adam(params, lr=args.learning_rate, eps=args.eps)
     criterion = nn.BCEWithLogitsLoss()
 
-    for epoch in range(args.num_epochs):
+    for epoch in range(args.epochs):
         train(train_loader, model, optimizer, criterion, args, epoch)
         validate(valid_loader, model, args, args.device, epoch)