evaluation/example_usage.sh

#!/bin/bash

MODEL_ID="nvidia/Nemotron-4-Mini-Hindi-4B-Instruct"
DATA_FOLDER="ChatRAG-Hi/data"
OUTPUT_FOLDER="ChatRAG-Hi/results"

echo "Running full pipeline for all datasets"
python run_all_evaluation.py \
    --mode full \
    --model-id "$MODEL_ID" \
    --data-folder "$DATA_FOLDER" \
    --output-folder "$OUTPUT_FOLDER" \
    --all-datasets \
    --device cuda \
    --num-ctx 5 \
    --max-tokens 64 \
    --limit 10 

echo "Evaluate specific dataset subset"
python run_all_evaluation.py \
    --mode full \
    --model-id "$MODEL_ID" \
    --data-folder "$DATA_FOLDER" \
    --output-folder "$OUTPUT_FOLDER" \
    --datasets doc2dial quac inscit \
    --device cuda

echo "Evaluation only (predictions already exist)"
python run_all_evaluation.py \
    --mode evaluation \
    --model-id "$MODEL_ID" \
    --data-folder "$DATA_FOLDER" \
    --output-folder "$OUTPUT_FOLDER" \
    --all-datasets


echo "Direct evaluation with get_scores.py"
python get_scores.py \
    --results-dir "$OUTPUT_FOLDER" \
    --data-path "$DATA_FOLDER" \
    --datasets doc2dial quac qrecc inscit hybridial doqa_cooking doqa_travel doqa_movies convfinqa \
    --output-csv "${OUTPUT_FOLDER}/scores.csv"