import streamlit as st from subpages.page import Context, Page from utils import AgGrid, aggrid_interactive_table @st.cache def get_loss_by_token(df_tokens): return ( df_tokens.groupby("tokens")[["losses"]] .agg(["count", "mean", "median", "sum"]) .droplevel(level=0, axis=1) # Get rid of multi-level columns .sort_values(by="sum", ascending=False) .reset_index() ) @st.cache def get_loss_by_label(df_tokens): return ( df_tokens.groupby("labels")[["losses"]] .agg(["count", "mean", "median", "sum"]) .droplevel(level=0, axis=1) .sort_values(by="mean", ascending=False) .reset_index() ) class LossesPage(Page): name = "Loss by Token/Label" icon = "sort-alpha-down" def render(self, context: Context): st.title(self.name) with st.expander("💡", expanded=True): st.write("Show count, mean and median loss per token and label.") col1, _, col2 = st.columns([8, 1, 6]) with col1: st.subheader("💬 Loss by Token") st.session_state["_merge_tokens"] = st.checkbox( "Merge tokens", value=True, key="merge_tokens" ) loss_by_token = ( get_loss_by_token(context.df_tokens_merged) if st.session_state["merge_tokens"] else get_loss_by_token(context.df_tokens_cleaned) ) aggrid_interactive_table(loss_by_token.round(3)) # st.subheader("🏷️ Loss by Label") # loss_by_label = get_loss_by_label(df_tokens_cleaned) # st.dataframe(loss_by_label) st.write( "_Attention: This statistic disregards that tokens have contextual representations._" ) with col2: st.subheader("🏷️ Loss by Label") loss_by_label = get_loss_by_label(context.df_tokens_cleaned) AgGrid(loss_by_label.round(3), height=200)