Update app.py

app.py

@@ -126,7 +126,7 @@ def lossFN(outs, targets):
 
 opt = TRNSFM.AdamW(params=mod.parameters(), lr=LEARNING_RATE)
 
-# Finetuning
+# Training and Finetuning
 def train(mod, training_loader):
     mod.train()
     for _, data in tqdm(enumerate(training_loader, 0)):
@@ -144,13 +144,13 @@ def train(mod, training_loader):
 
 # StreamLit Table of Results
 st.title("Finetuned Model for Toxicity")
-st.subheader("Model: distilbert-base-uncased")
+st.subheader("Model: bert-base-uncased")
 
 def predict(tweets):
     mod.eval()
     res = []
     with torch.no_grad():
-        for ins in test_loader_strings:
+        for ins in testing_loader:
             outs = mod(input_ids=ins['input_ids'].to(device), attention_mask=ins['attention_mask'].to(device), token_type_ids=ins['token_type_ids'].to(device))
             probs = torch.softmax(outs[0], dim=-1)
             preds = torch.argmax(probs, dim=-1)