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BLEnD / evaluation /evaluate.sh
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#!/bin/bash
# Define model keys
MODEL_KEYS=(
"gpt-4-1106-preview"
"gpt-3.5-turbo-1106"
"aya-101"
"gemini-pro"
"claude-3-opus-20240229"
"claude-3-sonnet-20240229"
"claude-3-haiku-20240307"
"Qwen1.5-72B-Chat"
"Qwen1.5-14B-Chat"
"Qwen1.5-32B-Chat"
"text-bison-002"
"c4ai-command-r-v01"
"c4ai-command-r-plus"
)
# Define countries and languages as an associative array
declare -A COUNTRY_LANG
COUNTRY_LANG["UK"]="English"
COUNTRY_LANG["US"]="English"
COUNTRY_LANG["South_Korea"]="Korean"
COUNTRY_LANG["Algeria"]="Arabic"
COUNTRY_LANG["China"]="Chinese"
COUNTRY_LANG["Indonesia"]="Indonesian"
COUNTRY_LANG["Spain"]="Spanish"
COUNTRY_LANG["Iran"]="Persian"
COUNTRY_LANG["Mexico"]="Spanish"
COUNTRY_LANG["Assam"]="Assamese"
COUNTRY_LANG["Greece"]="Greek"
COUNTRY_LANG["Ethiopia"]="Amharic"
COUNTRY_LANG["Northern_Nigeria"]="Hausa"
COUNTRY_LANG["Azerbaijan"]="Azerbaijani"
COUNTRY_LANG["North_Korea"]="Korean"
COUNTRY_LANG["West_Java"]="Sundanese"
# Prompt numbers
PROMPT_NUMBERS=("inst-4" "pers-3")
# Iterate over models, countries, languages, and prompts
for model_key in "${MODEL_KEYS[@]}"; do
for country in "${!COUNTRY_LANG[@]}"; do
language="${COUNTRY_LANG[$country]}"
for prompt_no in "${PROMPT_NUMBERS[@]}"; do
python evaluate.py --model "$model_key" \
--language "$language" \
--country "$country" \
--prompt_no "$prompt_no" \
--id_col ID \
--question_col Translation \
--response_col response \
--annotation_filename "${country}_data.json" \
--annotations_key "annotations" \
--evaluation_result_file "evaluation_results.csv"
if [ "$language" != "English" ]; then
python evaluate.py --model "$model_key" \
--language "English" \
--country "$country" \
--prompt_no "$prompt_no" \
--id_col ID \
--question_col Translation \
--response_col response \
--annotation_filename "${country}_data.json" \
--annotations_key "annotations" \
--evaluation_result_file "evaluation_results.csv"
fi
done
done
done