model output

app.py

@@ -180,14 +180,12 @@ st.markdown("## Try it out!")
 
 # select climate claim
 option_claim = st.selectbox('Select a climate claim to test', ex_df['claim'].unique())
-st.write('You selected:', option_claim)
 
 # filter df to selected claim
 filtered_df = ex_df[ex_df['claim'] == option_claim]
 
 # select evidence
 option_evidence = st.selectbox('Select evidence to test', filtered_df['evidence'].unique())
-st.write('You selected:', option_evidence)
 
 st.markdown("Now, we can use your selected (claim, evidence) pair in the fine-tuned transformer!")
 
@@ -213,7 +211,7 @@ with torch.no_grad():
    	pred_label = 'refutes'
 
    # write out
-   st.write("**is**", labels[0])
+   st.write("**is**", pred_label)
    st.write("**with**", option_evidence)
 
    # clean up true label
@@ -224,7 +222,7 @@ with torch.no_grad():
    	true_label = "supports"
    else:
    	true_label == "refutes"
-   	
+
    st.write("**The correct relationship is**", true_label)
 
 # section 6: analysis
@@ -232,7 +230,7 @@ st.markdown("## Critical Analysis")
 st.markdown("What else could we do?")
 st.markdown("* Given more data, the performance of the model can be greatly improved. This is just a proof of concept")
 st.markdown("* This is only one small part of the puzzle!")
-st.markdown("In the complete pipeline (from user input to final output), we could move from just outputting evidence to training a transformer to reply with persuasive evidence. That is, instead of simply saying, \"This claim is supported by this evidence\", the model could transform the evidence into a persuasive argument, thus combatting climate change misinfo in a more platable and convincing way.")
+st.markdown("* In the complete pipeline (from user input to final output), we could move from just outputting evidence to training a transformer to reply with persuasive evidence. That is, instead of simply saying, \"This claim is supported by this evidence\", the model could transform the evidence into a persuasive argument, thus combatting climate change misinfo in a more platable and convincing way.")
 
 
 # References + Resource Links