Spaces:
Runtime error
Runtime error
Fix QA mapping
Browse files
app.py
CHANGED
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@@ -30,7 +30,7 @@ TASK_TO_ID = {
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"summarization": 8,
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}
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-
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###########
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@@ -58,8 +58,8 @@ selected_dataset = st.selectbox("Select a dataset", all_datasets, index=all_data
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st.experimental_set_query_params(**{"dataset": [selected_dataset]})
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# TODO: In general this will be a list of multiple configs => need to generalise logic here
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metadata = get_metadata(selected_dataset)
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if metadata is None:
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st.warning("No evaluation metadata found. Please configure the evaluation job below.")
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@@ -67,8 +67,8 @@ with st.expander("Advanced configuration"):
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## Select task
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selected_task = st.selectbox(
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"Select a task",
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-
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index=
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)
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### Select config
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configs = get_dataset_config_names(selected_dataset)
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@@ -192,6 +192,8 @@ with st.expander("Advanced configuration"):
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col_mapping[target_col] = "target"
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elif selected_task == "extractive_question_answering":
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with col1:
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st.markdown("`context` column")
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st.text("")
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@@ -213,26 +215,22 @@ with st.expander("Advanced configuration"):
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context_col = st.selectbox(
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"This column should contain the question's context",
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col_names,
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index=col_names.index(get_key(
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)
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question_col = st.selectbox(
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"This column should contain the question to be answered, given the context",
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col_names,
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index=col_names.index(get_key(
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)
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answers_text_col = st.selectbox(
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"This column should contain example answers to the question, extracted from the context",
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col_names,
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index=col_names.index(get_key(
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if metadata is not None
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else 0,
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)
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answers_start_col = st.selectbox(
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"This column should contain the indices in the context of the first character of each answers.text",
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col_names,
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index=col_names.index(get_key(
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if metadata is not None
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else 0,
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)
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col_mapping[context_col] = "context"
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col_mapping[question_col] = "question"
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@@ -302,7 +300,7 @@ with st.form(key="form"):
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f"""
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Evaluation takes appoximately 1 hour to complete, so grab a β or π΅ while you wait:
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* π Click [here](https://huggingface.co/spaces/
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"""
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)
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else:
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"summarization": 8,
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}
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SUPPORTED_TASKS = list(TASK_TO_ID.keys())
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###########
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st.experimental_set_query_params(**{"dataset": [selected_dataset]})
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metadata = get_metadata(selected_dataset)
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print(metadata)
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if metadata is None:
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st.warning("No evaluation metadata found. Please configure the evaluation job below.")
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## Select task
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selected_task = st.selectbox(
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"Select a task",
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SUPPORTED_TASKS,
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index=SUPPORTED_TASKS.index(metadata[0]["task_id"]) if metadata is not None else 0,
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)
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### Select config
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configs = get_dataset_config_names(selected_dataset)
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col_mapping[target_col] = "target"
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elif selected_task == "extractive_question_answering":
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col_mapping = metadata[0]["col_mapping"]
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col_mapping = {k.replace("-", "."): v.replace("-", ".") for k, v in col_mapping.items()}
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with col1:
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st.markdown("`context` column")
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st.text("")
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context_col = st.selectbox(
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"This column should contain the question's context",
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col_names,
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index=col_names.index(get_key(col_mapping, "context")) if metadata is not None else 0,
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)
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question_col = st.selectbox(
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"This column should contain the question to be answered, given the context",
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col_names,
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index=col_names.index(get_key(col_mapping, "question")) if metadata is not None else 0,
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)
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answers_text_col = st.selectbox(
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"This column should contain example answers to the question, extracted from the context",
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col_names,
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index=col_names.index(get_key(col_mapping, "answers.text")) if metadata is not None else 0,
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)
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answers_start_col = st.selectbox(
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"This column should contain the indices in the context of the first character of each answers.text",
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col_names,
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index=col_names.index(get_key(col_mapping, "answers.answer_start")) if metadata is not None else 0,
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)
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col_mapping[context_col] = "context"
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col_mapping[question_col] = "question"
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f"""
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Evaluation takes appoximately 1 hour to complete, so grab a β or π΅ while you wait:
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* π Click [here](https://huggingface.co/spaces/autoevaluate/leaderboards) to view the results from your submission
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"""
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)
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else:
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